Copper cluster regulated by N, B atoms for enhanced CO2 electroreduction to formate.

Electrochemical CO2 conversion into formate by intermittent renewable electricity, presents a captivating prospect for both the storage of renewable electrical energy and the utilization of emitted CO2. Typically, Cu-based catalysts in CO2 reduction reactions favor the production of CO and other by-products. However, we have shifted this selectivity by incorporating B, N co-doped carbon (BNC) in the fabrication of Cu clusters. These Cu clusters are regulated with B, N atoms in a porous carbon matrix (Cu/BN-C), and Zn2+ ions were added to achieve Cu clusters with the diameter size of ∼1.0 nm. The obtained Cu/BN-C possesses a significantly improved catalytic performance in CO2 reduction to formate with a Faradaic efficiency (FE) of up to 70 % and partial current density (jformate) surpassing 20.8 mA cm-2 at -1.0 V vs RHE. The high FE and jformate are maintained over a 12-hour. The overall catalytic performance of Cu/BN-C outperforms those of the other investigated catalysts. Based on the density functional theory (DFT) calculation, the exceptional catalytic behavior is attributed to the synergistic effect between Cu clusters and N, B atoms by modulating the electronic structure and enhancing the charge transfer properties, which promoted a preferential adsorption of HCOO* over COOH*, favoring formate formation.

Application of graph neural network in computational heterogeneous catalysis.

Heterogeneous catalysis, as a key technology in modern chemical industries, plays a vital role in social progress and economic development. However, its complex reaction process poses challenges to theoretical research. Graph neural networks (GNNs) are gradually becoming a key tool in this field as they can intrinsically learn atomic representation and consider connection relationship, making them naturally applicable to atomic and molecular systems. This article introduces the basic principles, current network architectures, and datasets of GNNs and reviews the application of GNN in heterogeneous catalysis from accelerating the materials screening and exploring the potential energy surface. In the end, we summarize the main challenges and potential application prospects of GNNs in future research endeavors.

Molecular Engineering of Poly(Ionic Liquid) for Direct and Continuous Production of Pure Formic Acid from Flue Gas.

Electrochemical CO2 reduction reaction (CO2RR) offers a promising approach to close the carbon cycle and reduce reliance on fossil fuels. However, traditional decoupled CO2RR processes involve energy-intensive CO2 capture, conversion, and product separation, which increases operational costs. Here, we report the development of a bismuth-poly(ionic liquid) (Bi-PIL) hybrid catalyst that exhibits exceptional electrocatalytic performance for CO2 conversion to formate. The Bi-PIL catalyst achieves over 90% Faradaic efficiency for formate over a wide potential range, even at low 15% v/v CO2 concentrations typical of industrial flue gas. The biphenyl in PIL backbone affords hydrophobicity while maintaining high ionic conductivity, effectively mitigating the flooding issues. The PIL layer plays a crucial role as a CO2 concentrator and co-catalyst that accelerates the CO2RR kinetics. Furthermore, we demonstrate the potential of Bi-PIL catalysts in a solid-state electrolyte (SSE) electrolyzer for the continuous and direct production of pure formic acid solutions from flue gas. Techno-economic analysis suggests that this integrated process can produce formic acid at a significantly reduced cost compared to the traditional decoupled approaches. This work presents a promising strategy to overcome the challenges associated with low-concentration CO2 utilization and streamline the production of valuable liquid fuels and chemicals from CO2.

Sublimation Transformation Synthesis of Dual-Atom Fe Catalysts for Efficient Oxygen Reduction Reaction.

Dual-atom catalysts (DACs) have garnered significant interest due to their remarkable catalytic reactivity. However, achieving atomically precise control in the fabrication of DACs remains a major challenge. Herein, we developed a straightforward and direct sublimation transformation synthesis strategy for dual-atom Fe catalysts (Fe2/NC) by utilizing in situ generated Fe2Cl6(g) dimers from FeCl3(s). The structure of Fe2/NC was investigated by aberration-corrected transmission electron microscopy and X-ray absorption fine structure (XAFS) spectroscopy. As-obtained Fe2/NC, with a Fe-Fe distance of 0.3 nm inherited from Fe2Cl6, displayed superior oxygen reduction performance with a half-wave potential of 0.90 V (vs. RHE), surpassing commercial Pt/C catalysts, Fe single-atom catalyst (Fe1/NC), and its counterpart with a common and shorter Fe-Fe distance of ~0.25 nm (Fe2/NC-S). Density functional theory (DFT) calculations and microkinetic analysis revealed the extended Fe-Fe distance in Fe2/NC is crucial for the O2 adsorption on catalytic sites and facilitating the subsequent protonation process, thereby boosting catalytic performance. This work not only introduces a new approach for fabricating atomically precise DACs, but also offers a deeper understanding of the intermetallic distance effect on dual-site catalysis.

A Long-Range Disordering RuO2 Catalyst for Highly Efficient Acidic Oxygen Evolution Electrocatalysis.

Non-iridium acid-stabilized electrocatalysts for oxygen evolution reaction (OER) are crucial to reducing the cost of proton exchange membrane water electrolyzers (PEMWEs). Here, we report a strategy to modulate the stability of RuO2 by doping boron (B) atoms, leading to the preparation of a RuO2 catalyst with long-range disorder (LD-B/RuO2). The structure of long-range disorder endowed LD-B/RuO2 with a low overpotential of 175 mV and an ultra-long stability, which can maintain OER for about 1.6 months at 10 mA cm-2 current density in 0.5 M H2SO4 with almost invariable performance. More importantly, a PEM electrolyzer using LD-B/RuO2 as the anode demonstrated excellent performance, reaching 1000 mA cm-2 at 1.63 V with durability exceeding 300 h at 250 mA cm-2 current density. The introduction of B atoms induced the formation of a long-range disordered structure and symmetry-breaking B-Ru-O motifs, which enabled the catalyst structure to a certain toughness while simultaneously inducing the redistribution of electrons on the active center Ru, which jointly promoted and guaranteed the activity and long-term stability of LD-B/RuO2. This study provides a strategy to prepare long-range disordered RuO2 acidic OER catalysts with high stability using B-doping to perturb crystallinity, which opens potential possibilities for non-iridium-based PEMWE applications.

Gray matter structural alterations of cortico-striato-thalamo-cortical loop in familial Paroxysmal Kinesigenic Dyskinesia.

Background: Previous studies have indicated that patients with Paroxysmal Kinesigenic Dyskinesia (PKD) exhibit reduced gray matter volume in certain brain regions within the cortico-striato-thalamo-cortical (CSTC) loop. However, a comprehensive investigation specifically targeting the CSTC loop in PKD has never been conducted. Objectives: To provide evidence for the involvement of the CSTC loop in the pathogenesis of PKD from the perspective of structural alterations, this study carried out a surface-based morphometry (SBM), voxel-based morphometry (VBM), and structural covariance networks (SCN) combined analysis in familial PKD patients. Methods: A total of 8 familial PKD patients and 10 healthy family members were included in the study and underwent Brain MRI examinations. Based on 3D T1 MPRAGE data, neuroimaging metrics of cortical thickness from SBM, subcortical nuclei volume from VBM, and covariance coefficient from SCN were used to systematically investigate the brain structural alterations along the CSTC loop of PKD patients. Results: A significant decrease in the average cortical thickness of the left S1 region in the PKD group was observed. The volumes of subcortical nuclei, including the thalamus, putamen, and globus pallidus were reduced, with a pronounced effect observed in the bilateral putamen. And the structural covariance connection between the left putamen and the left globus pallidus was significantly strengthened. Conclusions: The study confirms the involvement of the CSTC loop in the pathogenesis of PKD from the perspective of structural alterations, and the findings may provide potential targets for objective diagnosis and therapeutic monitoring of PKD.

Association between sleep regularity and arterial stiffness among middle-age adults in Southwestern China.

BACKGROUND: Sleep regularity has been linked to a risk of arterial stiffness (AS). However, the association between sleep regularity indicators, which reflect 24-hour sleep variability, and AS has not yet been examined. METHODS: We analyzed data from 516 adults, aged 40-65 years (the median age of 51 years), from the 'Follow-up Study of Sleep Characteristics and Chronic Diseases in the Middle-aged and Elderly Population in Guizhou Province'. Participants underwent assessments of AS (OMRON HBP-8000, baPWV ≥ 1400 cm/s) and sleep (wrist smart band (Honor band 5i) for ≥ 7 days). Logistic regression was utilized to evaluate the odds ratio (OR) and 95% confidence interval (CI) of the association between sleep regularity and AS. RESULTS: A total of 516 people were included in this study, of which 279 (54.07%) were in the AS group. The univariate results showed that the AS group (Median 71.18) had lower SRI compared to the No-AS group (Median 75.00) (p < 0.001). The multifactorial results showed participants with higher SRI scores were more likely to have a lower risk of AS compared to those with lower SRI scores (ORQ4 VS. Q1=0.46, 95%CI: 0.25-0.85, p = 0.013). The SRI effect was more pronounced in male (ORQ4 VS. Q1=0.28, 95%CI: 0.12-0.69, p = 0.005), snoring populations (ORQ4 VS. Q1=0.13, 95%CI: 0.04-0.48, p = 0.002), and non-retired populations (ORQ4 VS. Q1=0.45, 95%CI: 0.22-0.92, p = 0.028). CONCLUSIONS: The present findings indicated that the effect between SRI and AS may be more sensitive than the standard deviation of sleep duration as well as the standard deviation of sleep onset.

Long-term exposure to low-level ozone and the risk of hypertension: A prospective cohort study conducted in a low-pollution region of southwestern China.

BACKGROUND: The current evidence regarding the association between long-term exposure to ozone (O3) and hypertension incidence is limited and inconclusive, particularly at low O3 concentrations. Therefore, our research aims to investigate the potential link between long-term O3 exposure and hypertension in a region with low pollution levels. METHODS: From 2010 to 2012, we conducted a cohort prospective study by recruiting nearly 10,000 attendees through multistage cluster random sampling in Guizhou Province, China. These individuals were followed up from 2016 to 2020, and 5563 cases were finally included in the analysis. We employed a high-resolution model with both temporal and spatial accuracy to estimate the maximum daily 8-h average O3 and utilized annual average O3 concentrations for three exposure periods (2009_10, 2007_10, 2005_10) as the exposure indicator. Time-dependent covariates Cox regression model was exerted to estimate the hazard ratios (HRs) of hypertension incidence. Generalized linear model was employed to assess the association between O3 and systolic, diastolic, pulse, and mean arterial pressure. The dose-response curve was explored using a restricted cubic spline function. RESULTS: 1213 hypertension incidents occurred during 39,001.80 person-years, with an incidence density of 31.10/1000 Person Years (PYs). The average O3 concentrations during the three exposure periods were 66.76 µg/m3, 67.85 µg/m3, and 67.21 µg/m3, respectively. Per 1 µg/m3 increase in O3 exposure was associated with 11 % increase in the incidence of hypertension in the single-pollution model, and the association was more pronounced in Han, urban, and higher altitude areas. SBP, PP, and MAP were increased by 0.619 (95 % CI, 0.361-0.877) mm Hg, 0.477 (95 % CI, 0.275-0.679) mm Hg, 0.301 (95 % CI, 0.127-0.475) mm Hg, respectively. Furthermore, we observed a nonlinear exposure-response relationship between O3 and hypertension incidence. CONCLUSIONS: Long-term exposure to low-level O3 exposure is associated with an increased risk of hypertension.

Designing the framework structure of noble-metal based nanoalloy catalysts driving redox electrocatalysis.

Noble metal-based nanoalloys (NAs) with different entropies have great potential in the field of energy and catalysis. However, it is still very difficult for the reported synthesis strategies to achieve the universal synthesis of small-sized alloys with controllable morphology. Here we develop a general synthesis strategy that combined cation exchange and spatial confinement (CESC). We used this method to construct a library with 21 NAs having low to high entropies. Importantly, we also demonstrate that the method can controllably achieve framing of almost all the NAs obtained, which can be realized by adjusting the amount of non-precious metals, despite the differences in the number of elements. Moreover, the CESC method showed outstanding ability to suppress the sintering of NAs and regulate the particle size of NAs. In the NA library, the framed PtCu/HCN as a redox electrocatalyst shows superior properties. For the methanol oxidation reaction (MOR), the specific and mass activities (7.02 mA cm-2 and 2.81 A mgPt -1) of PtCu/HCN show 28.1- and 13.4-fold enhancement compared to those of commercial Pt/C, and the peak current density is only attenuated by 5% after 50k seconds of chronoamperometry. For the hydrogen evolution reaction (HER), it can operate at ultralow overpotential (23.5 mV and 10 mA cm-2) for 150 h, far exceeding most of the reported catalysts. Moreover, the catalyst is capable of long-term hydrogen evolution at ultra-low overpotentials. Our work offers opportunities for synthesizing framed superfine noble metal-based NAs with different entropies.

Acyl-CoA Thioesterase 8 (ACOT8) is a Poor Prognostic Biomarker in Breast Cancer.

Purpose: This study aimed to investigate the expression of Acyl-CoA thioesterase 8 (ACOT8) in breast cancer (BC) and its association with clinicopathological characteristics, patient survival, and immune infiltration. Methods: We conducted a comprehensive analysis of ACOT8 mRNA differential expression across various cancer types, followed by survival analysis. We focused on BC, where ACOT8 expression was evaluated at both the mRNA and protein levels using online databases, qRT-PCR, and immunohistochemistry. Associations between ACOT8 expression and clinicopathological parameters were assessed using different databases. Additionally, we investigated the prognostic significance of ACOT8 in BC patients by analyzing various cohorts and databases. Furthermore, we predicted a potential signaling pathway and identified miR-1-3p as a possible upstream regulator of ACOT8. Finally, the relationship between ACOT8 and immune system infiltration, as well as immune checkpoint molecules, was examined. Results: Our findings demonstrated upregulated ACOT8 mRNA and protein levels in BC. Elevated ACOT8 expression correlated positively with various clinicopathological characteristics, indicating an unfavorable prognosis for patients. Functional enrichment analysis suggested ACOT8 involvement in lipid metabolism, mitochondrial components, and ribosomal functions. Moreover, we identified connections between ACOT8 and immune system markers, immune cell infiltration, and immune checkpoints. Conclusion: This study provides compelling evidence for ACOT8 upregulation in BC and its association with clinicopathological features and patient outcomes. Additionally, our findings suggest that targeting ACOT8 and immune checkpoints might enhance the effectiveness of immunotherapy in BC patients.

Highly Selective Electrocatalytic CO2 Conversion to Tailored Products through Precise Regulation of Hydrogenation and C-C Coupling.

The electrochemical reduction reaction of carbon dioxide (CO2RR) into valuable products offers notable economic benefits and contributes to environmental sustainability. However, precisely controlling the reaction pathways and selectively converting key intermediates pose considerable challenges. In this study, our theoretical calculations reveal that the active sites with different states of copper atoms (1-3-5-7-9) play a pivotal role in the adsorption behavior of the *CHO critical intermediate. This behavior dictates the subsequent hydrogenation and coupling steps, ultimately influencing the formation of the desired products. Consequently, we designed two model electrocatalysts comprising Cu single atoms and particles supported on CeO2. This design enables controlled *CHO intermediate transformation through either hydrogenation with *H or coupling with *CO, leading to a highly selective CO2RR. Notably, our selective control strategy tunes the Faradaic efficiency from 61.1% for ethylene (C2H4) to 61.2% for methane (CH4). Additionally, the catalyst demonstrated a high current density and remarkable stability, exceeding 500 h of operation. This work not only provides efficient catalysts for selective CO2RR but also offers valuable insights into tailoring surface chemistry and designing catalysts for precise control over catalytic processes to achieve targeted product generation in CO2RR technology.

Ligand-tuning copper in coordination polymers for efficient electrochemical C-C coupling.

Cu catalyses electrochemical CO2 reduction to valuable multicarbon products but understanding the structure-function relationship has remained elusive due to the active Cu sites being heterogenized and under dynamic re-construction during electrolysis. We herein coordinate Cu with six phenyl-1H-1,2,3-triazole derivatives to form stable coordination polymer catalysts with homogenized, single-site Cu active sites. Electronic structure modelling, X-ray absorption spectroscopy, and ultraviolet-visible spectroscopy show a widely tuneable Cu electronics by modulating the highest occupied molecular orbital energy of ligands. Using CO diffuse reflectance Fourier transform infrared spectroscopy, in-situ Raman spectroscopy, and density functional theory calculations, we find that the binding strength of *CO intermediate is positively correlated to highest occupied molecular orbital energies of the ligands. As a result, we enable a tuning of C-C coupling efficiency-a parameter we define to evaluate the efficiency of C2 production-in a broad range of 0.26 to 0.86. This work establishes a molecular platform that allows for studying structure-function relationships in CO2 electrolysis and devises new catalyst design strategies appliable to other electrocatalysis.

Hexa-atom Pt Catalyst Fabricated by a Ligand Engineering Strategy for Efficient Hydrogen Oxidation Reaction.

Atomically precise supported nanocluster catalysts (APSNCs), which feature exact atomic composition, well-defined structures, and unique catalytic properties, offer an exceptional platform for understanding the structure-performance relationship at the atomic level. However, fabricating APSNCs with precisely controlled and uniform metal atom numbers, as well as maintaining a stable structure, remains a significant challenge due to uncontrollable dispersion and easy aggregation during synthetic and catalytic processes. Herein, we developed an effective ligand engineering strategy to construct a Pt6 nanocluster catalyst stabilized on oxidized carbon nanotubes (Pt6/OCNT). The structural analysis revealed that Pt6 nanoclusters in Pt6/OCNT were fully exposed and exhibited a planar structure. Furthermore, the obtained Pt6/OCNT exhibited outstanding acidic HOR performances with a high mass activity of 18.37 A ⋅ mgpt -1 along with excellent stability during a 24 h constant operation and good CO tolerance, surpassing those of the commercial Pt/C. Density functional theory (DFT) calculations demonstrated that the unique geometric and electronic structures of Pt6 nanoclusters on OCNT altered the hydrogen adsorption energies on catalytic sites and thus lowered the HOR theoretical overpotential. This work presents a new prospect for designing and synthesizing advanced APSNCs for efficient energy electrocatalysis.

Associations between individual and mixed urinary metal exposure and dyslipidemia among Chinese adults: Data from the China Multi-Ethnic Cohort Study.

The prevalence of dyslipidemia is increasing, and it has become a significant global public health concern. Some studies have demonstrated contradictory relationships between urinary metals and dyslipidemia, and the combined effects of mixed urinary metal exposure on dyslipidemia remain ambiguous. In this study, we examined how individual and combined urinary metal exposure are associated with the occurrence of dyslipidemia. According to the data from the 2018-2019 baseline survey database of the China Multi-Ethnic Cohort (CMEC) Study, a population of 9348 individuals was studied. Inductively coupled plasmamass spectrometry (ICP-MS) was used to measure 21 urinary metal concentrations in the collected adult urinary samples. The associations between urinary metals and dyslipidemia were analyzed by logistic regression, weighted quantile sum regression (WQS), and quantile-based g-computation (qgcomp), controlled for potential confounders to examine single and combined effects. Dyslipidemia was detected in 3231 individuals, which represented approximately 34.6 % of the total population. According to the single-exposure model, Al and Na were inversely associated with the risk of dyslipidemia (OR = 0.95, 95 % CI: 0.93, 0.98; OR = 0.89, 95 % CI: 0.83, 0.95, respectively), whereas Zn, Ca, and P were positively associated (OR = 1.69, 95 % CI: 1.42, 2.01; OR = 1.12, 95 % CI: 1.06, 1.18; OR = 1.21, 95 % CI: 1.09, 1.34, respectively). Moreover, Zn and P were significantly positively associated even after adjusting for these metals, whereas Al and Cr were negatively associated with the risk of dyslipidemia. The results of the WQS and qgcomp analyses showed that urinary metal mixtures were positively associated with the risk of dyslipidemia (OR = 1.26, 95 % CI: 1.15, 1.38; OR = 1.09, 95 % CI: 1.01, 1.19). This positive association was primarily driven by Zn, P, and Ca. In the sensitivity analyses with collinearity diagnosis, interaction, and stratified analysis, the results remained, confirming the reliability of the study findings. In this study, the individual and combined effects of urinary Zn, P, and Ca on dyslipidemia were determined, which provided novel insights into the link between exposure to metals and dyslipidemia.

Hydrogen Peroxide Spillover on Platinum-Iron Hybrid Electrocatalyst for Stable Oxygen Reduction.

Iron-nitrogen-carbon (Fe-N-C) catalysts, although the most active platinum-free option for the cathodic oxygen reduction reaction (ORR), suffer from poor durability due to the Fe leaching and consequent Fenton effect, limiting their practical application in low-temperature fuel cells. This work demonstrates an integrated catalyst of a platinum-iron (PtFe) alloy planted in an Fe-N-C matrix (PtFe/Fe-N-C) to address this challenge. This novel catalyst exhibits both high-efficiency activity and stability, as evidenced by its impressive half-wave potential (E1/2) of 0.93 V versus reversible hydrogen electrode (vs RHE) and minimal 7 mV decay even after 50,000 potential cycles. Remarkably, it exhibits a very low hydrogen peroxide (H2O2) yield (0.07%) at 0.6 V and maintains this performance with negligible change after 10,000 potential cycles. Fuel cells assembled with this cathode PtFe/Fe-N-C catalyst show exceptional durability, with only 8 mV voltage loss at 0.8 A cm-2 after 30,000 cycles and ignorable current degradation at a voltage of 0.6 V over 85 h. Comprehensive in situ experiments and theoretical calculations reveal that oxygen species spillover from Fe-N-C to PtFe alloy not only inhibits H2O2 production but also eliminates harmful oxygenated radicals. This work paves the way for the design of highly efficient and stable ORR catalysts and has significant implications for the development of next-generation fuel cells.

Rapid emergence of latent knowledge in the sensory cortex drives learning.

Rapid learning confers significant advantages to animals in ecological environments. Despite the need for speed, animals appear to only slowly learn to associate rewarded actions with predictive cues1-4. This slow learning is thought to be supported by a gradual expansion of predictive cue representation in the sensory cortex2,5. However, evidence is growing that animals learn more rapidly than classical performance measures suggest6-8, challenging the prevailing model of sensory cortical plasticity. Here, we investigated the relationship between learning and sensory cortical representations. We trained mice on an auditory go/no-go task that dissociated the rapid acquisition of task contingencies (learning) from its slower expression (performance)7. Optogenetic silencing demonstrated that the auditory cortex (AC) drives both rapid learning and slower performance gains but becomes dispensable at expert. Rather than enhancement or expansion of cue representations9, two-photon calcium imaging of AC excitatory neurons throughout learning revealed two higher-order signals that were causal to learning and performance. First, a reward prediction (RP) signal emerged rapidly within tens of trials, was present after action-related errors only early in training, and faded at expert levels. Strikingly, silencing at the time of the RP signal impaired rapid learning, suggesting it serves an associative and teaching role. Second, a distinct cell ensemble encoded and controlled licking suppression that drove the slower performance improvements. These two ensembles were spatially clustered but uncoupled from underlying sensory representations, indicating a higher-order functional segregation within AC. Our results reveal that the sensory cortex manifests higher-order computations that separably drive rapid learning and slower performance improvements, reshaping our understanding of the fundamental role of the sensory cortex.

The role of P3H family in cancer: implications for prognosis, tumor microenvironment and drug sensitivity.

Introduction: Prolyl 3-hydroxylases (P3H) are crucial enzymes in collagen biosynthesis and are known to be involved in a variety of physiological processes. However, their specific roles in cancer progression, modulation of the tumor microenvironment (TME), and impact on patient prognosis remain areas that require further investigation. Methods: The investigation involved a comprehensive analysis of expression profiles and clinical data obtained from the Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) databases. This included the assessment of genetic variation, gene expression, and the prognostic significance of P3H family genes. P3H scores were calculated using various databases and R-based tools, followed by correlation analyses with the TME, immune cell infiltration, drug sensitivity and immunotherapy.Variations in P3H gene expression patterns were observed across different tumor types and prognoses, suggesting that most genes within the family were risk factors, especially P3H1 and P3H4. The P3H score was associated with immune infiltration and drug resistance. Notably, individuals with elevated expression of P3H2, P3H3, and CRTAP exhibited higher resistance to multiple anti-tumor drugs. Results: P3H family proteins play diverse roles in cancer progression, significantly impacting patient prognosis and the effectiveness of immunotherapy. Conclusions: The P3H score, identified as a potential biomarker for evaluating TME, holds promise in guiding precision medicine strategies.

Synthesis, Structure and Antibacterial Activity of Two Novel Coordination Polymers Based on N,N'-bis(4-carbozvlbenzvl)-4-aminotoluene and Heterocyclic Ligand against S. aureus.

As the use of antibiotics increases, the increasing resistance of bacteria is the main reason for the reduced efficiency of antibacterial drugs, making the research of new antibacterial materials become new hot spot. In this article, two novel coordination polymers (CPs), namely, [Cd2(L)2(bibp)2]n (1) and [Ni(L)(bib)]n (2), where H2L = N,N'-bis(4-carbozvlbenzvl)-4-aminotoluene, bibp = 4,4'-bis(imidazol-1-yl)biphenyl, and bib = 1,3-bis(1-imidazoly)benzene, have been synthesized under solvothermal and hydrothermal condition. Structural clarification was performed through infrared spectrum and single-crystal X-ray diffraction analysis, while thermal analysis and XRD technology were used for the performance assessment of compounds 1 and 2. In addition, antibacterial performance experiments showed that compounds 1 and 2 have certain selectivity in their antibacterial properties and have good antibacterial properties against S. aureus. As the concentration of the compound increases, the inhibitory effect gradually strengthens, and when the concentration of the compound reaches 500 µg/mL and 400 µg/mL, the concentration of the S. aureus solution no longer increases and has been completely inhibited.

Lattice Oxygen Activation through Deep Oxidation of Co4N by Jahn-Teller-Active Dopants for Improved Electrocatalytic Oxygen Evolution.

Triggering the lattice oxygen oxidation mechanism is crucial for improving oxygen evolution reaction (OER) performance, because it could bypass the scaling relation limitation associated with the conventional adsorbate evolution mechanism through the direct formation of oxygen-oxygen bond. High-valence transition metal sites are favorable for activating the lattice oxygen, but the deep oxidation of pre-catalysts suffers from a high thermodynamic barrier. Here, taking advantage of the Jahn-Teller (J-T) distortion induced structural instability, we incorporate high-spin Mn3+ ( t 2 g 3 e g 1 ${{t}_{2g}^{3}{e}_{g}^{1}}$ ) dopant into Co4N. Mn dopants enable a surface structural transformation from Co4N to CoOOH, and finally to CoO2, as observed by various in situ spectroscopic investigations. Furthermore, the reconstructed surface on Mn-doped Co4N triggers the lattice oxygen activation, as evidenced experimentally by pH-dependent OER, tetramethylammonium cation adsorption and online electrochemical mass spectrometry measurements of 18O-labelled catalysts. In general, this work not only offers the introducing J-T effect approach to regulate the structural transition, but also provides an understanding about the influence of the catalyst's electronic configuration on determining the reaction route, which may inspire the design of more efficient catalysts with activated lattice oxygen.

Predicting lung function decline in cystic fibrosis: the impact of initiating ivacaftor therapy.

BACKGROUND: Modulator therapies that seek to correct the underlying defect in cystic fibrosis (CF) have revolutionized the clinical landscape. Given the heterogeneous nature of lung disease progression in the post-modulator era, there is a need to develop prediction models that are robust to modulator uptake. METHODS: We conducted a retrospective longitudinal cohort study of the CF Foundation Patient Registry (N = 867 patients carrying the G551D mutation who were treated with ivacaftor from 2003 to 2018). The primary outcome was lung function (percent predicted forced expiratory volume in 1 s or FEV1pp). To characterize the association between ivacaftor initiation and lung function, we developed a dynamic prediction model through covariate selection of demographic and clinical characteristics. The ability of the selected model to predict a decline in lung function, clinically known as an FEV1-indicated exacerbation signal (FIES), was evaluated both at the population level and individual level. RESULTS: Based on the final model, the estimated improvement in FEV1pp after ivacaftor initiation was 4.89% predicted (95% confidence interval [CI]: 3.90 to 5.89). The rate of decline was reduced with ivacaftor initiation by 0.14% predicted/year (95% CI: 0.01 to 0.27). More frequent outpatient visits prior to study entry and being male corresponded to a higher overall FEV1pp. Pancreatic insufficiency, older age at study entry, a history of more frequent pulmonary exacerbations, lung infections, CF-related diabetes, and use of Medicaid insurance corresponded to lower FEV1pp. The model had excellent predictive accuracy for FIES events with an area under the receiver operating characteristic curve of 0.83 (95% CI: 0.83 to 0.84) for the independent testing cohort and 0.90 (95% CI: 0.89 to 0.90) for 6-month forecasting with the masked cohort. The root-mean-square errors of the FEV1pp predictions for these cohorts were 7.31% and 6.78% predicted, respectively, with standard deviations of 0.29 and 0.20. The predictive accuracy was robust across different covariate specifications. CONCLUSIONS: The methods and applications of dynamic prediction models developed using data prior to modulator uptake have the potential to inform post-modulator projections of lung function and enhance clinical surveillance in the new era of CF care.