The vasculogenic mimicry related signature predicts the prognosis and immunotherapy response in renal clear cell carcinoma.

BACKGROUND: Clear cell carcinoma of the kidney is a common urological malignancy characterized by poor patient prognosis and treatment outcomes. Modulation of vasculogenic mimicry in tumor cells alters the tumor microenvironment and the influx of tumor-infiltrating lymphocytes, and the combination of its inducers and immune checkpoint inhibitors plays a synergistic role in enhancing antitumor effects. METHODS: We downloaded the data from renal clear cell carcinoma samples and vasculogenic mimicry-related genes to establish a new vasculogenic mimicry-related index (VMRI) using a machine learning approach. Based on VMRI, patients with renal clear cell carcinoma were divided into high VMRI and low VMRI groups, and patients' prognosis, clinical features, tumor immune microenvironment, chemotherapeutic response, and immunotherapeutic response were systematically analyzed. Finally, the function of CDH5 was explored in renal clear cell carcinoma cells. RESULTS: VMRI can be used for prognostic and immunotherapy efficacy prediction in a variety of cancers, which consists of four vasculogenic mimicry-related genes (CDH5, MMP9, MAPK1, and MMP13), is a reliable predictor of survival and grade in patients with clear cell carcinoma of the kidney and has been validated in multiple external datasets. We found that the high VMRI group presented higher levels of immune cell infiltration, which was validated by pathological sections. We performed molecular docking prediction of vasculogenic mimicry core target proteins and identified natural small molecule drugs with the highest affinity for the target protein. Knockdown of CDH5 inhibited the proliferation and migration of renal clear cell carcinoma. CONCLUSIONS: The VMRI identified in this study allows for accurate prognosis assessment of patients with renal clear cell carcinoma and identification of patient populations that will benefit from immunotherapy, providing valuable insights for future precision treatment of patients with renal clear cell carcinoma.

Ultrastable Anion Radicals in Ligand-Dimerized Frameworks for Self-Accumulated Electrochemiluminescence.

Electrochemiluminescence (ECL) is a light-emitting process that occurs via an annihilation reaction among energetic radical intermediates, whose stabilities determine the ECL efficiency. In this study, a ligand-dimerized metal-organic framework (MOF) with ultrastable anion radical is designed as an efficient nanoemitter for self-accumulated ECL. Due to the nonplanar structure of perylene diimide (PDI) derivate, two PDI ligands in the framework form a J-dimer unit with a vertical distance of ∼5.74 Å. In cathodic scanning, the ligand-dimerized MOF demonstrates three-step ECL emissions with a gradual increase in ECL intensity. Unlike the decrease in the PDI ligand, the self-accumulated ECL of the MOF was observed with 16.8-fold enhancement due to the excellent stability of radical intermediates in frameworks. Electron paramagnetic resonance demonstrated the ultrastability of free radicals in the designed frameworks, with 82.2% remaining even after one month of storage. Density functional theory calculations supported that PDI dimerization was energetically favorable upon successive electron injection. Moreover, the ECL wavelength is 610 nm, corresponding to the emission of excited dimers. The radical-stabilized reticular nanoemitters open up a new platform for decoding the fundamentals of self-accumulated ECL systems.

Tailoring Titanium Carbide Clusters for New Materials: from Met-Cars to Carbon-Doped Superatoms.

Tailoring materials with prescribed properties and regular structures is a critical and challenging research topic. Early transition metals were found to form supermagic M8C12 metallocarbohedrenes (Met-Cars); however, stable metal carbides are not limited to this common stoichiometry. Utilizing self-developed deep-ultraviolet laser ionization mass spectrometry, here, we report a strategy to generate new titanium carbides by reacting pure Tin clusters with acetylene. Interestingly, two products corresponding to Ti17C2 and Ti19C10 exhibit superior abundances in addition to the Ti8C12 Met-Cars. Using global-minimum search, the structures of Ti17C2 and Ti19C10 are determined to be an ellipsoidal D4d and a rod-shaped D5h geometry, respectively, both with carbon-capped Ti4C moieties and superatomic features. We illustrate the electronic structures and bonding nature in these carbon-doped superatoms concerning their enhanced stability and local aromaticity, shedding light on a new class of metal-carbide nanomaterials with atomic precision.

Prognostic value of preoperative combined with postoperative systemic immune-inflammation index for disease-free survival after radical rectal cancer surgery: a retrospective cohort study.

Background: Colorectal cancer (CRC) ranks highly in malignant tumor incidence and mortality rates, severely affecting human health. The predictive value of the systemic immune-inflammation index (SII) in CRC prognosis is gaining attention, but there is limited research on the combined preoperative and postoperative SII. This study aims to explore the prognostic value of combined SII on disease-free survival (DFS) in patients undergoing radical surgery for rectal cancer. Methods: We enrolled 292 patients with rectal cancer who underwent radical resection at the Affiliated Hospital of Xuzhou Medical University from May 2018 to September 2020, along with regular follow-ups to document the DFS. Patients' complete blood cell counts were assessed before surgery and between 21-56 days postoperatively. Calculating preoperative and postoperative SII, patients were categorized into four groups based on the optimal cutoff values: (I) low-low group (preoperative SII <449.325 and postoperative SII <568.13); (II) high-low group (preoperative SII ≥449.325 and postoperative SII <568.13); (III) low-high group (preoperative SII <449.325 and postoperative SII ≥568.13); and (IV) high-high group (preoperative SII ≥449.325 and postoperative SII ≥568.13). The receiver operating characteristic (ROC) curve analysis evaluated the prediction efficacy of preoperative, postoperative, and combined SII. Kaplan-Meier analysis generated DFS curves, and Cox regression analysis determined prognostic factors. Results: With a median follow-up of 41 months, 65.4% (191/292) patients reached DFS. The clinical pathological features between the four groups are balanced and comparable (P>0.05). The area under the ROC curve for preoperative, postoperative, and combined SII was 0.668 [95% confidence interval (CI): 0.6-0.737], 0.696 (95%CI: 0.63-0.763), and 0.741 (95% CI: 0.681-0.802), respectively. After adjusting for confounding factors such as adjuvant therapy, differentiation, vascular invasion, neural invasion, tumor-node-metastasis (TNM) stage, carcinoembryonic antigen (CEA), and carbohydrate antigen 19-9 (CA19-9), significant differences were observed between the high-low group [hazard ratio (HR) =2.403; 95% CI: 1.255-4.602; P=0.008], low-high group (HR =5.058; 95% CI: 2.389-10.71; P<0.001), and high-high group (HR =6.214; 95% CI: 3.474-11.115; P<0.001) compared to the low-low group, with higher risks of adverse outcomes. Conclusions: Combined SII has better predictive efficacy than monitoring preoperative or postoperative SII alone in rectal cancer patients undergoing radical surgery.

The Synergistic Effect between Metal and Sulfur Vacancy to Boost CO2 Reduction Efficiency: A Study on Descriptor Transferability and Activity Prediction.

Both metal center active sites and vacancies can influence the catalytic activity of a catalyst. A quantitative model to describe the synergistic effect between the metal centers and vacancies is highly desired. Herein, we proposed a machine learning model to evaluate the synergistic index, PSyn, which is learned from the possible pathways for CH4 production from CO2 reduction reaction (CO2RR) on 26 metal-anchored MoS2 with and without sulfur vacancy. The data set consists of 1556 intermediate structures on metal-anchored MoS2, which are used for training. The 2028 structures from the literature, comprising both single active site and dual active sites, are used for external test. The XGBoost model with 3 features, including electronegativity, d-shell valence electrons of metal, and the distance between metal and vacancy, exhibited satisfactory prediction accuracy on limiting potential. Fe@Sv-MoS2 and Os@MoS2 are predicted to be promising CO2RR catalysts with high stability, low limiting potential, and high selectivity against hydrogen evolution reactions (HER). Based on some easily accessible descriptors, transferability can be achieved for both porous materials and 2D materials in predicting the energy change in the CO2RR and nitrogen reduction reaction (NRR). Such a predictive model can also be applied to predict the synergistic effect of the CO2RR in other oxygen and tungsten vacancy systems.

Sandwiched Epitaxy Growth of 2D Single-Crystalline Hexagonal Bismuthene Nanoflakes for Electrocatalytic CO2 Reduction.

Two-dimensional (2D) bismuthene is predicted to possess intriguing physical properties, but its preparation remains challenging due to the high surface energy constraint. Herein, we report a sandwiched epitaxy growth strategy for the controllable preparation of 2D bismuthene between a Cu foil substrate and a h-BN covering layer. The top h-BN layer plays a crucial role in suppressing the structural transformation of bismuthene and compensating for the charge transfer from the bismuthene to the Cu(111) surface. The bismuthene nanoflakes present a superior thermal stability up to 500 °C in air, attributed to the passivation effect of the h-BN layer. Moreover, the bismuthene nanoflakes demonstrate an ultrahigh faradaic efficiency of 96.3% for formate production in the electrochemical CO2 reduction reaction, which is among the highest reported for Bi-based electrocatalysts. This study offers a promising approach to simultaneously synthesize and protect 2D bismuthene nanoflakes, which can be extended to other 2D materials with a high surface energy.

Network pharmacology and molecular docking to explore the mechanism of Sheng Xue Bao mixture against iron deficiency anemia.

Based on network pharmacology and molecular docking, we investigated the mechanism of action of Sheng Xue Bao mixture (SXBM) in treating iron deficiency anemia (IDA). We screened the HERB and traditional Chinese medicine systems pharmacology database and analysis platform databases to identify the active ingredients and targets of SXBM. The targets associated with "iron deficiency anemia" were collected from GeneCards, TTD, and OMIM databases. A component-target interaction network was constructed using Cytoscape 3.8.2. The protein-protein interaction network of candidate targets was generated using the STRING database and visualized with Cytoscape 3.8.2 software. Core modules obtained from clustering analysis were subjected to Gene Ontology and Kyoto encyclopedia of genes and genomes enrichment analysis. Finally, molecular docking validation of key targets and active components was performed using Autodock Vina software. A total of 174 active components and 111 genes were identified as potential active components and targets for IDA treatment, including quercetin, kaempferol, luteolin, beta-sitosterol, and other flavonoids as main active components. Gene Ontology enrichment analysis show that interleaved genes are enriched in 2328 biological processes, 71 cellular component expression processes, and 157 molecular function processes. Kyoto encyclopedia of genes and genomes analysis mainly envolved Prostate cancer, Hepatitis B, Kaposi sarcoma-associated herpesvirus infection, Endocrine resistance, Lipid and atherosclerosis, Central carbon metabolism in cancer, Human cytomegalovirus infection and HIF-1 signaling pathway. STAT3, SRC, PIK3R1, and GRB2 were selected as core targets. The molecular docking results demonstrated strong interactions between key components and their respective target proteins. Network pharmacological analysis suggested that SXBM could treat IDA by regulating various biological processes and related signaling pathways. It laid the foundation for further elucidating the molecular mechanism of SXBM treatment of IDA.

A Self-Templated Design Approach toward Multivariate Metal-Organic Frameworks for Enhanced Oxygen Evolution.

Multivariate metal-organic framework (MOF) is an ideal electrocatalytic material due to the synergistic effect of multiple metal active sites. In this study, a series of ternary M-NiMOF (M = Co, Cu) through a simple self-templated strategy that the Co/Cu MOF isomorphically grows in situ on the surface of NiMOF is designed. Owing to the electron rearrange of adjacent metals, the ternary CoCu-NiMOFs demonstrate the improved intrinsic electrocatalytic activity. At optimized conditions, the ternary Co3 Cu-Ni2 MOFs nanosheets give the excellent oxygen evolution reaction (OER) performance of current density of 10 mA cm-2 at low overpotential of 288 mV with a Tafel slope of 87 mV dec-1 , which is superior to that of bimetallic nanosheet and ternary microflowers. The low free energy change of potential-determining step identifies that the OER process is favorable at Cu-Co concerted sites along with strong synergistic effect of Ni nodes. Partially oxidized metal sites also reduce the electron density, thus accelerating the OER catalytic rate. The self-templated strategy provides a universal tool to design multivariate MOF electrocatalysts for highly efficient energy transduction.

Planar Chirality for Acid/Base Responsive Macrocyclic Pillararenes Induced by Amino Acid Derivatives: Molecular Dynamics Simulations and Machine Learning.

Chirality is ubiquitous in nature, ranging from a DNA helix to a biological macromolecule, snail's shell, and even a galaxy. However, the precise control of chirality at the nanoscale is a challenge due to the structure complexity of supramolecular assemblies, the small energy differences between different enantiomers, and the difficulty in obtaining polymorphic crystals. The planar chirality of water-soluble pillar[5]arenes (called WP5-Na with Na ions in the side chain) host triggered by the addition of chiral L-amino acid hydrochloride (L-AA-OEt) guests and acid/base is rationalized by the relative stability of different chiral isomers, being estimated by molecular dynamics (MD) simulations and quantum chemical calculations. As an increase in the pH value, the change from a positive to a negative value of the free energy difference (ΔG) between two conformations, pR-WP5-Na⊃L-AA-OEt and pS-WP5-Na⊃L-AA-OEt, suggests an inversed preference of the pS-WP5-Na conformer induced by the deprotonated L-arginine ethyl ester (L-Arg-OEt) at pH = 14, which is supported by the circular dichroism (CD) experiments. On the basis of 2256 WP5-Na⊃L-Ala-OEt and 3299 WP5-Na⊃L-Arg-OEt conformers sampled from MD, the gradient boosting regression (GBR) model exhibits a satisfactory performance (R2 = 0.91) in predicting the chirality of WP5-Na complexations using host-guest binding descriptors, including the geometry matching and binding sites and modes (electrostatics and hydrogen bonding). The machine learning model also performs well on external tests of different hosts (using different side chains and cavity sizes) with the addition of 22 other different guests, with the average chirality prediction accuracy of ML versus experimental CD determinations of 92.8%. The easily accessible host-guest features, binding position coordination and size matching between the cavity and guest, exhibit a close correlation to the chirality of different macrocyclic molecules, water-soluble pillar[6]arenes (WP6) versus WP5, in complexation with different amino acid guests. The exploration of efficient host-guest features in ML displays the great potential of building a large space of various assembled systems and accelerating the on-demand design of chiral supramolecular systems at the nanoscale.

Highly Efficient Electrochemical Nitrate Reduction to Ammonia in Strong Acid Conditions with Fe2 M-Trinuclear-Cluster Metal-Organic Frameworks.

Nitrate-containing industrial wastewater poses a serious threat to the global food security and public health safety. As compared to the traditional microbial denitrification, electrocatalytic nitrate reduction shows better sustainability with ultrahigh energy efficiency and the production of high-value ammonia (NH3 ). However, nitrate-containing wastewater from most industrial processes, such as mining, metallurgy, and petrochemical engineering, is generally acidic, which contradicts the typical neutral/alkaline working conditions for both denitrifying bacteria and the state-of-the-art inorganic electrocatalysts, leading to the demand for pre-neutralization and the problematic hydrogen evaluation reaction (HER) competition and catalyst dissolution. Here, we report a series of Fe2 M (M=Fe, Co, Ni, Zn) trinuclear cluster metal-organic frameworks (MOFs) that enable the highly efficient electrocatalytic nitrate reduction to ammonium under strong acidic conditions with excellent stability. In pH=1 electrolyte, the Fe2 Co-MOF demonstrates the NH3 yield rate of 20653.5 µg h-1 mg-1 site with 90.55 % NH3 -Faradaic efficiency (FE), 98.5 % NH3 -selectivity and up to 75 hr of electrocatalytic stability. Additionally, successful nitrate reduction in high-acidic conditions directly produce the ammonium sulfate as nitrogen fertilizer, avoiding the subsequent aqueous ammonia extraction and preventing the ammonia spillage loss. This series of cluster-based MOF structures provide new insights into the design principles of high-performance nitrate reduction catalysts under environmentally-relevant wastewater conditions.

Spinel-Derived Formation and Amorphization of Bimetallic Oxyhydroxides for Efficient Electrocatalytic Biomass Oxidation.

Replacing the oxygen evolution reaction (OER) with water-assisted oxidation of organic molecules represents a promising approach for achieving sustainable electrochemical biomass utilization. Among numerous OER catalysts, spinels have received substantial attention due to their manifold compositions and valence states, yet their application in biomass conversions remains rare. Herein, a series of spinels were investigated for the selective electrooxidation of furfural and 5-hydroxymethylfurfural, two model substrates for versatile value-added chemical products. Spinel sulfides universally exhibit superior catalytic performance compared to that of spinel oxides, and further investigations show that the replacement of oxygen with sulfur led to the complete phase transition of spinel sulfides into amorphous bimetallic oxyhydroxides during electrochemical activation, serving as the active species. Excellent values of conversion rate (100%), selectivity (100%), faradaic efficiency (>95%), and stability were achieved via sulfide-derived amorphous CuCo-oxyhydroxide. Furthermore, a volcano-like correlation was established between their BEOR and OER activities based on an OER-assisted organic oxidation mechanism.

Improvement in the healing of bone fractures using a cyclodextrin/Ni-MOF nanofibers network: the development of a novel substrate to increase the surface area with desirable functional properties.

In this study, a ß-cyclodextrins (ß-CDs)/Ni-based MOF (ß-CDs/Ni-based MOF) fibrous network with focus on biocompatible and biodegradable properties was used as a new material for orthopedic applications. The final products were synthesized by an efficient, rapid, and controllable electrospinning route under optimal conditions, including a flow rate of 0.3 mL g-1, applied voltage of 18 kV, and spinning distance of 20 cm. Efficient characterization by various analyzes showed that the ß-CDs/Ni-based MOF fibrous nanostructures had a thermal stability at about 320 °C and homogeneous particles with a narrow size distribution. The BET analysis results showed a specific surface area of 2140 m2 g-1 for these compounds, which facilized potential conditions needed for the application of these compounds as a new substrate to improve the healing of bone fractures. The results showed the better porosity of the ß-CDs/Ni-based MOF scaffolds as an essential property, leading to higher proliferation and nutrition and oxygen delivery, resulting in more tissue regeneration. This study proposes a novel strategy for a fibrous network substrate with distinct properties for orthopedic purposes.

Covalent organic frameworks with Ni-Bis(dithiolene) and Co-porphyrin units as bifunctional catalysts for Li-O2 batteries.

The rational design of efficient and stable catalysts for the oxygen reduction reaction and oxygen evolution reaction (ORR/OER) is the key to improving Li-O2 battery performance. Here, we report the construction of ORR/OER bifunctional cathode catalysts in a covalent organic framework (COF) platform by simultaneously incorporating Ni-bis(dithiolene) and Co-porphyrin units. The resulting bimetallic Ni/Co-COF exhibits high surface area, fairly good electrical conductivity, and excellent chemical stability. Li-O2 batteries with the Ni/Co-COF-based cathode show a low discharge/charge potential gap (1.0 V) and stable cycling (200 cycles) at a current density of 500 mA g-1, rivaling that of PtAu nanocrystals. Density functional theory computations and control experiments using nonmetal or single metal-based isostructural COFs reveal the critical role of Ni and Co sites in reducing the discharge/charge overpotentials and regulating the Li2O2 deposition. This work highlights the advantage of bimetallic COFs in the rational design of efficient and stable Li-O2 batteries.

Photocatalytic nitrogen fixation under an ambient atmosphere using a porous coordination polymer with bridging dinitrogen anions.

The design of highly electron-active and stable heterogeneous catalysts for the ambient nitrogen reduction reaction is challenging due to the inertness of the N2 molecule. Here, we report the synthesis of a zinc-based coordination polymer that features bridging dinitrogen anionic ligands, {[Zn(L)(N2)0.5(TCNQ-TCNQ)0.5]·(TCNQ)0.5}n (L is tetra(isoquinolin-6-yl)tetrathiafulvalene and TCNQ is tetracyanoquinodimethane), and show that it is an efficient photocatalyst for nitrogen fixation under an ambient atmosphere. It exhibits an ammonia conversion rate of 140 µmol g-1 h-1 and functions well also with unpurified air as the feeding gas. Experimental and theoretical studies show that the active [Zn2+-(N≡N)--Zn2+] sites can promote the formation of NH3 and the detachment of the NH3 formed creates unsaturated [Zn2+···Zn+] intermediates, which in turn can be refilled by external N2 sequestration and fast intermolecular electron migration. The [Zn2+···Zn+] intermediates stabilized by the sandwiched cage-like donor-acceptor-donor framework can sustain continuous catalytic cycles. This work presents an example of a molecular active site embedded within a coordination polymer for nitrogen fixation under mild conditions.

Traditional Chinese Medicine Formula Jian Pi Tiao Gan Yin Reduces Obesity in Mice by Modulating the Gut Microbiota and Fecal Metabolism.

The current study employed the high-fat diet (HFD) induced murine model to assess the relationship between the effect of Jian Pi Tiao Gan Yin (JPTGY) and the alterations of gut microbiota and fecal metabolism. C57BL/6 mice were used to establish an animal model of obesity via HFD induce. Serum biochemical indicators of lipid metabolism were used to evaluate the pharmacodynamics of JPTGY in obese mice. Bacterial communities and metabolites in the feces specimens from the controls, the Group HFD, and the JPTGY-exposed corpulency group were studied by 16s rDNA genetic sequence in combination with liquid chromatography-mass spectrometry (LC-MS) based untargeted fecal metabolomics techniques. Results revealed that JPTGY significantly decreased the levels of total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), and elevated high-density lipoprotein cholesterol (HDL-C). Moreover, JPTGY could up-regulate the abundance and diversity of fecal microbiota, which was characterized by the higher phylum of proteobacteria. Consistently, at the genus levels, JPTGY supplementation induced enrichments in Lachnospiraceae NK4A136 group, Oscillibacter, Turicibacter, Clostridium sensu stricto 1, and Intestinimonas, which were intimately related to 14 pivotal fecal metabolins in respond to JPTGY therapy were determined. What is more, metabolomics further analyses show that the therapeutic effect of JPTGY for obesity involves linoleic acid (LA) metabolism paths, alpha-linolenic acid (ALA) metabolism paths, glycerophospholipid metabolism paths, arachidonic acid (AA) metabolism paths, and pyrimidine metabolism paths, which implied the potential mechanism of JPTGY in treating obesity. It was concluded that the linking of corpulency phenotypes with intestinal flora and fecal metabolins unveils the latent causal link of JPTGY in the treatment of hyperlipidemia and obesity.

An analysis of lncRNA-miRNA-mRNA networks to investigate the effects of HDAC4 inhibition on skeletal muscle atrophy caused by peripheral nerve injury.

Background: Muscle atrophy caused by peripheral nerve injury is a common clinical disease, with no effective treatments currently available. Our previous studies have found that denervation-induced muscle atrophy can be alleviated by inhibiting histone deacetylase 4 (HDAC4). An increasing amount of evidence shows that microRNA (miRNA) and long noncoding RNA (lncRNA) are involved in the occurrence of muscle atrophy. This study aimed to find the mechanism by which HDAC4 regulates denervation-induced muscle atrophy based on lncRNA-associated competing endogenous RNA (ceRNA) networks. Methods: We analyzed the influence of short hairpin RNA (shRNA) knockdown of HDAC4 on lncRNAs and miRNAs after denervated muscle atrophy using RNA sequencing. A Pearson's correlation heat map and principal component analysis were employed to analyze differentially expressed miRNAs and lncRNAs. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses of target genes were conducted. The ceRNA network of lncRNA-miRNA-mRNA was constructed, and the core regulatory molecules in the ceRNA network were analyzed. Results: We found 32 miRNAs and 111 lncRNAs related to denervated muscle atrophy regulated by HDAC4. Moreover, 15 downregulated lncRNAs, 14 upregulated miRNAs, and 61 downregulated mRNAs constituted a ceRNA regulatory network, participating in the biological processes including response to denervation involved in regulation of muscle adaptation, along with the signaling pathways including autophagy, FoxO signaling pathways, and Jak-STAT signaling pathways. Additionally, 6 upregulated lncRNAs, 8 downregulated miRNAs, and 66 upregulated mRNAs constituted another ceRNA regulatory network, which was mainly involved in cell cycle-related biological processes and pathways. Finally, 3 lncRNAs, 4 miRNAs, and 12 mRNAs constituted a ceRNA sub-network, and XR_377582.2 and ENSMUST00000143649 were considered to be the key lncRNAs. Conclusions: In the ceRNA network, all nodes are directly or indirectly involved in the process by which HDAC4 regulates skeletal muscle atrophy caused by peripheral nerve injury. XR_377582.2 and ENSMUST00000143649 may be the key lncRNAs related to HDAC4 involved in the regulation of muscle atrophy.

Batch-Scale Synthesis of Nanoparticle-Agminated Three-Dimensional Porous Cu@Cu2O Microspheres for Highly Selective Electrocatalysis of Nitrate to Ammonia.

The electrochemical nitrate reduction reaction (NITRR), which converts nitrate to ammonia, is promising for artificial ammonia synthesis at mild conditions. However, the lack of favorable electrocatalysts has hampered its large-scale applications. Herein, we report the batch-scale synthesis of three-dimensional (3D) porous Cu@Cu2O microspheres (Cu@Cu2O MSs) composed of fine Cu@Cu2O nanoparticles (NPs) using a convenient electric explosion method with outstanding activity and stability for the electrochemical reduction of nitrate to ammonia. Density functional theory (DFT) calculations revealed that the Cu2O (111) facets could facilitate the formation of *NO3H and *NO2H intermediates and suppress the hydrogen evolution reaction (HER), resulting in high selectivity for the NITRR. Moreover, the 3D porous structure of Cu@Cu2O MSs facilitates electrolyte penetration and increases the localized concentration of reactive species for the NITRR. As expected, the obtained Cu@Cu2O MSs exhibited an ultrahigh NH3 production rate of 327.6 mmol·h-1·g-1cat. (which is superior to that of the Haber-Bosch process with a typical NH3 yield <200 mmol h-1g-1cat.), a maximum Faradaic efficiency of 80.57%, and remarkable stability for the NITRR under ambient conditions. Quantitative 15N isotope labeling experiments indicated that the synthesized ammonia originated from the electrochemical reduction of nitrate. Achieving the batch-scale and low-cost production of high-performance Cu@Cu2O MSs electrocatalysts using the electric explosion method is promising for the large-scale realization of selective electrochemical reduction of nitrate toward artificial ammonia synthesis.

Identification of Single-Molecule Catecholamine Enantiomers Using a Programmable Nanopore.

Enantiomers, chiral isomers with opposite chirality, typically demonstrate differences in their pharmacological activity, metabolism, and toxicity. However, direct discrimination between enantiomers is challenging due to their similar physiochemical properties. Following the strategy of programmable nanoreactors for stochastic sensing (PNRSS), introduction of phenylboronic acid (PBA) to a Mycobacterium smegmatis porin A (MspA) assists in the identification of the enantiomers of norepinephrine and epinephrine. Using a machine learning algorithm, identification of the enantiomers has been achieved with an accuracy of 98.2%. The enantiomeric excess (ee) of a mixture of enantiomeric catecholamines was measured to determine the enantiomeric purity. This sensing strategy is a faster method for the determination of ee values than liquid chromatography-mass spectrometry and is useful as a quality control in the industrial production of enantiomeric drugs.

Discovery of Electronic Structure and Interfacial Interaction Features in Catalytic Activity.

The selective transformation of inert bonds (C-H, C-O, C-C, C-F, etc.) via various catalysts is one of the most challenging areas, with applications in organic synthesis, materials science, and biological and pharmaceutical chemistry. The catalytic performance of homogeneous and heterogeneous catalysts can be rationally controlled in two ways: (i) electronic structure modulation of the active site, such as the metal center, ligands, and coordination modes, to improve the catalytic activity and stability and (ii) tuning intermolecular or interfacial interactions to promoting the reaction kinetics by accelerating the transmission of electrons between the catalyst and solvents or support. The rational design of catalysts based on adjustable features, such as metal (monometallic or bimetallic) active sites, crystal phase, ligands, solvents, and supports for inert bond activation under mild conditions remains a challenge. This Perspective summarizes the features of electronic structures, interfacial interactions, and their effects on molecular catalysis, metal-organic frameworks (MOFs), and natural mineral catalysis. The discovery of efficient catalysts could be promoted using machine-learning methods with high-performance descriptors. More attention should be paid to high-throughput quantum-chemical computations and experiments, automatic searches of chemical reaction pathways, and efficient machine-learning or deep-learning methods to accelerate catalyst design and synthesis in the future.

Shengxuebao Mixture for Iron Deficiency Anemia: A Meta-Analysis and Systematic Review.

OBJECTIVE: Traditional Chinese medicine Shengxuebao Mixture (SXBM) has been approved for treating iron deficiency anemia (IDA) in China. This study aimed to collect evidence and quantify the effect of SXBM on IDA. METHODS: Seven online databases were surveyed up to July 13, 2021. Randomized controlled trials in which SXBM was combined with conventional therapies to treat IDA and compared with placebo or conventional therapies were included in the study. The red blood cell (RBC) count, hemoglobin (Hb) level, serum ferritin (SF) level, and adverse events rate (AER) were evaluated. RESULTS: A total of 1,108 patients from 8 trials were recruited. SXBM plus conventional therapy increased the Hb level (mean difference [MD] = 13.04, 95% confidence interval [CI] 8.37-17.7, p < 0.00001), RBC count (MD = 0.41, 95% CI 0.19-0.62, p = 0.002), SF level (MD = 6.25, 95% CI 2.88-9.62, p = 0.0003), and AER (risk ratio = 0.56, 95% CI 0.36-0.86; p = 0.008). CONCLUSIONS: SXBM combined with conventional treatment seemed to be beneficial for patients with IDA. However, the harmlessness of SXBM was not confirmed due to insufficient trials and low methodological quality. Follow-up clinical studies should be cautiously designed, and more research is needed.