Diastereoselective and Enantioselective Hydrophosphinylations of Conjugated Enynes, Allenes and Dienes via Synergistic Pd/Co Catalysis.

Different from the reported work focusing on the construction of single P- or C-stereocenter via hydrophosphinylation of unsaturated carbon bonds, the highly diastereo- and enantioselective hydrophosphinylation reaction of allenes, conjugated enynes and 1,3-dienes is achieved via a designed Pd/Co dual catalysis and newly modified masked phosphinylating reagent. A series of allyl motifs bearing both a tertiary C- and P-stereocenter are prepared in generally good yields, >20:1 dr, >20:1 rr and 99% ee. The unprecedented diastereo- and enantioselective hydrophosphinylation of 1,3-enynes is established to generate skeletons containing both a P-stereocenter and a nonadjacent chiral axis. The first stereodivergent hydrophosphinylation reaction is also developed to achieve all four P-containing stereoisomers. The present protocol features the use of only 3-minutes reaction time and 0.1% catalyst, and with the observation of up to 730 TON. A set of mechanistic studies reveal the necessity and roles of two metal catalysts and corroborate the designed synergistic process.

Enhanced angiogenesis in porous poly(ε-caprolactone) scaffolds fortified with methacrylated hyaluronic acid hydrogel after subcutaneous transplantation.

A composite scaffold composed of a porous scaffold and hydrogel filling can facilitate engraftment, survival, and retention in cell transplantation processes. This study presents a composite scaffold made of poly(ε-caprolactone) (PCL) and methacrylated hyaluronic acid (MeHA) hydrogel and describes the corresponding physical properties (surface area, porosity, and mechanical strength) and host response (angiogenesis and fibrosis) after subcutaneous transplantation. Specifically, we synthesise MeHA with different degrees of substitution and fabricate a PCL scaffold with different porosities. Subsequently, we construct a series of PCL/MeHA composite scaffolds by combining these hydrogels and scaffolds. In experiments with mice, the scaffold composed of 3% PCL and 10-100 kDa, degree of substitution 70% MeHA results in the least fibrosis and a higher degree of angiogenesis. This study highlights the potential of PCL/MeHA composite scaffolds for subcutaneous cell transplantation, given their desirable physical properties and host response.

Optimization of differentiation conditions for porcine adipose-derived mesenchymal stem cells and analysis of fatty acids in cultured fat.

Cultured fat is an important part of cultured meat, and the ability of adipose-derived mesenchymal stem cells (ADSCs) to differentiate into mature adipose tissue affects the quality of cultured fat. Thus, the primary aim of this study was to screen for combinations of differentiation-inducing factors (DIF) using single-factor experiment and orthogonal experimental design under two-dimensional culture conditions for ADSCs. The results showed that a combination of DIF consisting of 1 µmol/L dexamethasone, 0.1 mmol/L 3-isobutyl-1-methylxanthine, 10 µg/mL insulin, 0.1 mmol/L indomethacin, and 2 µmol/L rosiglitazone was a good choice for the differentiation of ADSCs. An combination of DIF was applied to the preparation of cultured fat with collagen as scaffolds. Forty-eight fatty acids were detected in cultured fat by ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). Among them, the content of twenty-one fatty acids in cultured fat was significantly higher than that of conventional porcine subcutaneous adipose tissue (P < 0.05), and the content of 14 fatty acids was not significantly different (P > 0.05). The ratio of ω-6 polyunsaturated fatty acids content to ω-3 polyunsaturated fatty acids content was 1.23:1, which meant cultured fat was beneficial for human health. This study provides a method to improve the differentiation ability of ADSCs while also providing a reference for indicating the nutritional value of cultured fat.

Concentrations and carbonyl index of microplastic in surface seawater in southeastern coastal region off Japan, Northwestern Pacific.

In this study, microplastic concentrations in the southeastern coastal regions of Japan were measured along the northward ocean current at seven stations from Okinawa to Tokai region. Concentrations ranged from 0.014 to 0.094 pieces/m3, except for a station near the Bungo Channel mouth, which had 0.723 pieces/m3. Polystyrene (PS) foam was most prevalent near the east side of Kyushu, suggesting origination from nearby coastal areas. Fragmentation levels were higher in the Tokai region. In addition, carbonyl index (CI) of polyethylene (PE) microplastics increased northward, indicating northward movement from southern regions. Standard PE microplastics showed chemical treatment does not significantly alter CI values. Further spectral analysis suggested potential oxidation of polypropylene (PP) and PS foam by chemical treatment. This study provides a comprehensive understanding of the abundance, distribution, and characteristics of microplastics in the southeastern coastal regions of Japan in the northwest Pacific, enhancing the understanding of environmental fate of microplastics.

Textured vegetable protein as a partial replacement for lean meat in salami analogues: Perspectives on physicochemical properties, flavour and proteome changes.

Integrating plant proteins into meat products offers a sustainable way to reduce the environmental impact of meat consumption while satisfying the growing flexitarian population. This study explored the effects of textured vegetable proteins (TVPs) on the physico-chemical attributes and flavour profile of hybrid salamis using 4D label-free proteomics. Results showed that hybrid salamis had lower pH, reduced water activity and increased weight loss compared with traditional salamis, along with greater hardness and a slightly rough, porous texture with a filamentous structure. TVPs substantially modified crucial meaty flavour compounds (nitrogen oxides, sulfides and pyrazine), increasing heightening sourness and bitterness while diminishing umami. Proteomic analysis revealed significant upregulation of myosin and actin in hybrid salamis; notably, these proteins were involved in glycerol-3-phosphate dehydrogenase activity and calcineurin-mediated signalling, underscoring their role in flavour enhancement. Therefore, hybrid salamis offer an attractive alternative to traditional salamis by merging meat-like taste and texture with plant protein.

Increased matrix stiffness in pituitary neuroendocrine tumors invading the cavernous sinus is activated by TAFs: focus on the mechanical signatures.

PURPOSE: Pituitary neuroendocrine tumors (PitNETs) with invasion of the cavernous sinus (CS) are particularly challenging to treat. Tumor associated fibroblasts (TAFs) are recognized for their pivotal role in reprogramming extracellular matrix (ECM). Herein, we aimed to explore the potential involvement of TAFs in ECM reprogramming and elucidate the underlying mechanism involved. METHODS: We applied dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to measure tumor vessel permeability and applied atomic force microscopy (AFM) to measure the matrix stiffness of PitNETs located in both CS and sella turcica (ST). Western blotting, immunofluorescence, immunohistochemistry, and quantitative RT-PCR were utilized to analyze the ECM components. Proteomic biochemical analysis was utilized to uncover potential mechanisms governing ECM dynamics. RESULTS: We found that PitNETs in the CS were stiffer than those in the ST. Increased ECM stiffness within the CS facilitated the acquisition of stem-like properties, enhanced proliferation, and induced epithelial-to-mesenchymal transition (EMT) of GH3 cells. Furthermore, the expression levels of lysyl oxidase (LOX), matrix metallopeptidase 2 (MMP2) and MMP9 in pituitary adenoma cells increased in the stiffer matrix. Proteomic analysis suggested TAFs were activated in the CS area and contributed enhanced matrix stiffness by secreting Col-1 and Col-3. Furthermore, mTOR pathway was activated under higher matrix stiffness and the migration and invasion of GH3 cells be repressed by mTOR inhibitor. CONCLUSION: These findings demonstrated that activated TAFs contributed to stiffer matrix and increased ECM stiffness stimulating mTOR pathway in pituitary tumor cells. Our study indicated that mTOR inhibitor was a promising treatment strategy from the standpoint of PitNET biomechanical properties.

An interpretable capacity prediction method for lithium-ion battery considering environmental interference.

Predicting the capacity of lithium-ion battery (LIB) plays a crucial role in ensuring the safe operation of LIBs and prolonging their lifespan. However, LIBs are easily affected by environmental interference, which may impact the precision of predictions. Furthermore, interpretability in the process of predicting LIB capacity is also important for users to understand the model, identify issues, and make decisions. In this study, an interpretable method considering environmental interference (IM-EI) for predicting LIB capacity is introduced. Spearman correlation coefficients, interpretability principles, belief rule base (BRB), and interpretability constraints are used to improve the prediction precision and interpretability of IM-EI. Dynamic attribute reliability is introduced to minimize the effect of environmental interference. The experimental results show that IM-EI model has good interpretability and high precision compared to the other models. Under interference conditions, the model still has good precision and robustness.

Chromosome-level genome assembly and annotation of Flueggea virosa (Phyllanthaceae).

Flueggea virosa (Roxb. ex Willd.) Royle, an evergreen shrub and small tree in the Phyllanthaceae family, holds significant potential in garden landscaping and pharmacological applications. However, the lack of genomic data has hindered further scientific understanding of its horticultural and medicinal values. In this study, we have assembled a haplotype-resolved genome of F. virosa for the first time. The two haploid genomes, named haplotype A genome and haplotype B genome, are 487.33 Mb and 477.53 Mb in size, respectively, with contig N50 lengths of 31.45 Mb and 32.81 Mb. More than 99% of the assembled sequences were anchored to 13 pairs of pseudo-chromosomes. Furthermore, 21,587 and 21,533 protein-coding genes were predicted in haplotype A and haplotype B genomes, respectively. The availability of this chromosome-level genome fills the gap in genomic data for F. virosa and provides valuable resources for molecular studies of this species, supporting future research on speciation, functional genomics, and comparative genomics within the Phyllanthaceae family.

Microplastic volumes in Tokyo Bay.

Microplastic (MP) pollution is a rising environmental concern. This study investigated MP concentrations in Tokyo Bay using neuston net for surface sampling and deep-sea plankton pump for underwater sampling across six stations at multiple depths. Results revealed substantial variation in MP concentrations. Surface large microplastics (LMP, > 350 µm) ranged from 0.21 × 10-3 to 3.34 × 10-3 pieces L-1, averaging 1.26 × 10-3 pieces L-1, while surface small microplastics (SMP, 60 µm to 350 µm) were highest at head of the bay (11.5 ± 3.05 pieces L-1). SMP concentrations varied with depth and position, peaking at center of the bay (5.79 ± 1.63 pieces L-1 at 2 m). Additionally, the total amount of surface LMP was estimated at 10.3 m3 and SMP at 15.0 m3 in the Tokyo Bay. This study provides a comprehensive picture of the spatial and vertical distribution of MP in Tokyo Bay.

An automatic method for accurate signal-to-noise ratio estimation and baseline correction of Raman spectra of environmental microplastics.

In this study, we introduced a k-iterative double sliding-window (DSW^k) method for the estimation of spectral noise, signal-to-noise ratio (SNR), and baseline correction. The performance was evaluated using simulated spectra and compared against other commonly employed methods. Convergent evaluation determined that a k value of 20 strikes an optimal balance between convergence and computational intensity. The DSW^k method demonstrated outstanding performance across different spectral types (flat baseline, baseline with elevation, baseline with fluctuation, baseline with elevation and fluctuation) coupled with SNR values from 10 to 1000, achieving results that ranged from 1.01 to 1.08 times of the reference value in estimating spectral noise. It also showed that the estimated SNR values are 0.89 to 0.93 times of the reference value, demonstrating a 74.5 % - 131.7 % improvement over the conventional method in spectra with elevated and/or fluctuating baselines. Additionally, the DSW^k method proved effective in correcting baselines and identifying polymers in environmental samples of polyethylene (PE), polypropylene (PP), and polystyrene (PS), despite the limitation of reducing the peak height in spectra with low SNR. This method offers the potential to enhance the automatic and accurate evaluation of spectral quality and could assist in the development of guidelines for more rapid parameter adjustments in Raman measurements.

A Neural Network Potential Energy Surface and Quantum Dynamics Study of Ca(1S) + H2(v 0 = 0, j 0 = 0) → CaH + H Reaction.

The reactive collision between Ca and H2 molecules has attracted great interest experimentally due to the key role of the product CaH molecule in the field of astrophysics and cold molecules. However, quantum dynamics calculations for this system have not been reported due to the lack of a global potential energy surface (PES). Herein, a globally accurate PES of the ground-state CaH2 is developed by combining 11365 high-level ab initio points and permutation invariant polynomial neural network method. Based on the newly constructed PES, the state-to-state quantum dynamics calculations for the Ca(1S) + H2 (v 0 = 0, j 0 = 0) → CaH + H reaction are carried out using the time-dependent wave packet method. The dynamic results reveal that the reaction follows the complex-forming mechanism near the reactive threshold, whereas both the indirect insertion mechanism and direct abstraction mechanism have effects at higher collision energies. The newly constructed PES can be used to further study the influence of isotope substitution, rovibrational excitation, and spatial orientation of reactant molecules on reaction dynamics.

A Globally Accurate Neural Network Potential Energy Surface and Quantum Dynamics Studies on Be+(2S) + H2/D2 → BeH+/BeD+ + H/D Reactions.

Chemical reactions between Be+ ions and H2 molecules have significance in the fields of ultracold chemistry and astrophysics, but the corresponding dynamics studies on the ground-state reaction have not been reported because of the lack of a global potential energy surface (PES). Herein, a globally accurate ground-state BeH2+ PES is constructed using the neural network model based on 18,657 ab initio points calculated by the multi-reference configuration interaction method with the aug-cc-PVQZ basis set. On the newly constructed PES, the state-to-state quantum dynamics calculations of the Be+(2S) + H2(v0 = 0; j0 = 0) and Be+(2S) + D2(v0 = 0; j0 = 0) reactions are performed using the time-dependent wave packet method. The calculated results suggest that the two reactions are dominated by the complex-forming mechanism and the direct abstraction process at relatively low and high collision energies, respectively, and the isotope substitution has little effect on the reaction dynamics characteristics. The new PES can be used to further study the reaction dynamics of the BeH2+ system, such as the effects of rovibrational excitations and alignment of reactant molecules, and the present dynamics data could provide an important reference for further experimental studies at a finer level.

Stereodynamic control of nonadiabatic processes in low-energy Be+(2P) + H2 (v = 0, j = 2) collisions.

Controlling the relative arrangement of colliding molecules is crucial for determining the dynamical outcomes of chemical processes and has emerged as a hot spot of experimental research. Here, the quantum scattering calculations are conducted to investigate the stereodynamic control in collisions between Be+(2P) and H2 (v = 0, j = 2), which undergo nonadiabatic transitions to the electronic ground state. Stereodynamic preparation is achieved by controlling the initial alignment of the H2 bond axis relative to the scattering frame. For product BeH+ in the reactive process, the differential cross sections (DCSs) are significantly enhanced in the forward and sideways hemispheres when the alignment angle ß is 60°. For the product H2 in the quenching channel, the ß = 0° preparation can result in a more than one-fold increase in the DCS at a polar scattering angle of 0°. Furthermore, varying the alignment angle ß also has noteworthy effects on the rotational-state distributions of BeH+ products. Specifically, ß = 0° preparation can induce the disappearance of the bimodal distribution of rotational states at a collision energy of 0.05 eV.

Optimization of Cohesive Parameters in the Interfacial Transition Zone of Rubberized Concrete Based on the Response Surface Method.

Rubber concrete has been applied to a certain extent in fatigue-resistant structures due to its good durability. Based on a cohesive model of rubber composed of a five-phase material containing mortar, aggregate, rubber, aggregate-mortar interfacial transition zone (ITZ), and rubber-mortar ITZ, this paper studies the influence of the cohesive parameters in the rubber-mortar ITZ on the fatigue problem of rubber concrete on the mesoscopic scale. As the weak part of cement-based composite materials, the ITZ has a great influence on the mechanical properties and durability of concrete, but the performance of the ITZ is difficult to test in macro experiments, resulting in difficulties in determining its simulation parameters. Based on the cohesive model with a rubber content of 5%, this study uses Monofactor analysis and the Plackett-Burman test to quickly and effectively determine the primary and secondary influences of the cohesive model parameters in the rubber-mortar ITZ; further, the response surface method is used to optimize the cohesive parameters in the rubber-mortar ITZ, and the numerical simulation results after optimizing the cohesive parameters are compared and analyzed with the simulation results before optimization. The results show that, under the setting of the optimized parameters, the simulation results of each item of the optimal cohesive model parameters in the rubber-mortar ITZ are in line with the reality and closer to the experimental data, and they are also applicable to rubber concrete models with different rubber dosing.

Ten-Year Follow-Up of Lung Cancer Patients with Resected Stage IA Invasive Non-Small Cell Lung Cancer.

OBJECTIVE: The purpose of this study was to assess 10-year follow-up outcomes after surgical resection in patients with stage IA invasive non-small cell lung cancer (NSCLC) based on postoperative pathological diagnosis. METHODS: Patients with stage IA invasive NSCLC who underwent resection between December 2008 and December 2013 were reviewed. Patients were categorized into the pure-ground glass opacity (pGGO), mixed-ground glass opacity (mGGO), and solid groups based on consolidation to tumor ratio (CTR). Postoperative survival and risk of recurrence and developing secondary primary lung cancer were analyzed in each group. RESULTS: Among the 645 stage IA invasive NSCLC, the 10-year overall survival and recurrence-free survival rate was 79.38% and 77.44%, respectively. The 10-year overall survival for pGGO, mGGO, and solid group of patients was 95.08%, 86.21%, and 72.39%, respectively. The respective recurrence-free survival rate was 100%, 89.82%, and 65.83%. Multivariable Cox regression analysis associated tumor size and GGO components with recurrence and younger age, and tumors with GGO components were associated with longer overall survival. The cumulative incidence curve indicated no recurrence of GGO lung cancer ≥ 5 years postoperatively. Our cohort indicated that the number and stations of dissected lymph node did not influence long-term prognosis of IA invasive NSCLC. CONCLUSIONS: Recurrence of invasive stage IA NSCLC with GGO was more prevalent in patients with tumor size >1 cm and CTR > 0.5, occurring within 5 years after surgery. This will provide important evidence for follow-up strategies in these patients.

Single-cell analysis of CD4+ tissue residency memory cells (TRMs) in adult atopic dermatitis: A new potential mechanism.

The pathophysiology of atopic dermatitis (AD) is complex. CD4+ T cells play an essential role in the development of lesions in AD. However, the underlying mechanism remains unclear. In the present study, we investigated the differentially expressed genes (DEGs) between adult AD lesioned and non-lesioned skin using two datasets from the Gene Expression Omnibus (GEO) database. 62 DEGs were shown to be related to cytokine response. Compared to non-lesioned skin, lesioned skin showed immune infiltration with increased numbers of activated natural killer (NK) cells and CD4+ T memory cells (p < 0.01). We then identified 13 hub genes with a strong association with CD4+ T cells using weighted correlation network analysis. Single-cell analysis of AD detected a novel CD4+ T subcluster, CD4+ tissue residency memory cells (TRMs), which were verified through immunohistochemistry (IHC) to be increased in the dermal area of AD. The significant relationship between CD4+ TRM and AD was assessed through further analyses. FOXO1 and SBNO2, two of the 13 hub genes, were characteristically expressed in the CD4+ TRM, but down-regulated in IFN-γ/TNF-α-induced HaCaT cells, as shown using quantitative polymerase chain reaction (qPCR). Moreover, SBNO2 expression was associated with increased Th1 infiltration in AD (p < 0.05). In addition, genes filtered using Mendelian randomization were positively correlated with CD4+ TRM and were highly expressed in IFN-γ/TNF-α-induced HaCaT cells, as determined using qPCR and western blotting. Collectively, our results revealed that the newly identified CD4+ TRM may be involved in the pathogenesis of adult AD.

The influence of stereodynamical control on the nonadiabatic effects in the D + HD (v = 1, j = 2) → D2 + H reaction.

Stereodynamics is a field that studies the influence of the alignment or orientation of colliding partners on the results of collisions. At present, the intersection of nonadiabatic effects and stereodynamics remains to be explored. In this study, we theoretically demonstrate significant stereodynamical effects in the D + HD (v = 1, j = 2) → D2 + H reaction within the collision energy range of 0.01-2.99 eV by using the time-dependent wave packet method. It is found that the stereodynamical control not only facilitates the reaction but also allows precise control of the products over a range of different scattering angles. The analysis at the state-to-state level reveals that the nonadiabatic effects are stronger in the parallel configuration than in the perpendicular configuration. By topological approach to separate the two reaction pathways at the conical intersection, the scattering amplitude of the roaming pathway in the parallel configuration is larger than that of the perpendicular configuration, which leads to more dramatic nonadiabatic features in the collision with parallel configuration.

In-depth understanding of transport behavior of sulfided nano zerovalent iron/reduced graphene oxide@guar gum slurry: Stability and mobility.

Nanoscale zero-valent iron (NZVI), which has the advantages of small particle size, large specific surface area, and high reactivity, is often injected into contaminated aquifers in the form of slurry. However, the prone to passivation and agglomeration as well as poor stability and mobility of NZVI limit the further application of this technology in fields. Therefore, sulfided NZVI loaded on reduced graphene oxide (S-NZVI/rGO) and guar gum (GG) with shear-thinning properties as stabilizers were used to synthesize S-NZVI/rGO@GG slurries. SEM, TEM, and FT-IR confirmed that the dispersion and anti-passivation of NZVI were optimized in the coupled system. The stability and mobility of the slurry were improved by increasing the GG concentration, enhancing the pH, and decreasing the ionic strength and the presence of Ca2+ ions, respectively. A modified advection-dispersion equation (ADE) was used to simulate the transport experiments considering the strain and physicochemical deposition/release. Meanwhile, colloidal filtration theory (CFT) demonstrated that Brownian motion plays a dominant role in the migration of S-NZVI/rGO@GG slurry, and the maximum migration distance can be increased by appropriately increasing the injection rate. Extended-Derjaguin-Landau-Verwey-Overbeek (XDLVO) theory showed that the excellent stability and migration of S-NZVI/rGO@GG slurry mainly came from the GG spatial forces. This study has important implications for the field injection of S-NZVI/rGO@GG slurry. According to the injection parameters, the injection range of S-NZVI/rGO@GG slurry is effectively controlled, which lays the foundation for the promotion of application in actual fields.

PLS-based gene subset augmentation and tumor-specific gene identification.

In the study of tumor disease pathogenesis, the identification of genes specifically expressed in disease states is pivotal, yet challenges arise from high-dimensional datasets with limited samples. Conventional gene (feature) selection methods often fall short of capturing the complexity of gene-phenotype and gene-gene interactions, necessitating a more robust analysis method. To address these challenges, a gene subset augmentation strategy is proposed in this paper. Our approach introduces diverse perturbation mechanisms to generate distinct gene subsets. The partial least squares-based multiple gene measurement algorithm considers gene-phenotype and gene-gene correlations, identifying differentially expressed genes, including those with weak signals. The constructed gene networks derived from the augmented subsets unveil regulatory patterns, enabling association analysis to explore gene associations comprehensively. Our algorithm excels in identifying small-sized gene subsets with strong discriminative power, surpassing traditional methods that yield a single gene subset. Unlike conventional approaches, our algorithm reveals a spectrum of different gene subsets and their weakly differentially expressed genes. This nuanced perspective aids in unraveling the molecular characteristics and specific expression patterns of tumor genes. The versatility of our approach not only contributes to the advancement of tumor-specific gene identification but also holds promise for addressing challenges in various fields characterized by high-dimensional datasets and limited samples. The Python implementation is available at http://github.com/wenjieyou/PLSGSA.

General Model for Predicting Response of Gas-Sensitive Materials to Target Gas Based on Machine Learning.

Gas sensors play a crucial role in various industries and applications. In recent years, there has been an increasing demand for gas sensors in society. However, the current method for screening gas-sensitive materials is time-, energy-, and cost-consuming. Consequently, an imperative exists to enhance the screening efficiency. In this study, we proposed a collaborative screening strategy through integration of density functional theory and machine learning. Taking zinc oxide (ZnO) as an example, the responsiveness of ZnO to the target gas was determined quickly on the basis of the changes in the electronic state and structure before and after gas adsorption. In this work, the adsorption energy and electronic and structural characteristics of ZnO after adsorbing 24 kinds of gases were calculated. These computed features served as the basis for training a machine learning model. Subsequently, various machine learning and evaluation algorithms were utilized to train the fast screening model. The importance of feature values was evaluated by the AdaBoost, Random Forest, and Extra Trees models. Specifically, charge transfer was assigned importance values of 0.160, 0.127, and 0.122, respectively, ranking as the highest among the 11 features. Following closely was the d-band center, which was presumed to exert influence on electrical conductivity and, consequently, adsorption properties. With 5-fold cross-validation using the Extra Tree accuracy, the 24-sample data set achieved an accuracy of 88%. The 72-sample data set achieved an accuracy of 78% using multilayer perceptron after 5-fold cross-validation, with both data sets exhibiting low standard deviations. This verified the accuracy and reliability of the strategy, showcasing its potential for rapidly screening a material's responsiveness to the target gas.