Facet-switching of rate-determining step on copper in CO2-to-ethylene electroreduction.

Reduction of carbon dioxide (CO2) by renewable electricity to produce multicarbon chemicals, such as ethylene (C2H4), continues to be a challenge because of insufficient Faradaic efficiency, low production rates, and complex mechanistic pathways. Here, we report that the rate-determining steps (RDS) on common copper (Cu) surfaces diverge in CO2 electroreduction, leading to distinct catalytic performances. Through a combination of experimental and computational studies, we reveal that C─C bond-making is the RDS on Cu(100), whereas the protonation of *CO with adsorbed water becomes rate-limiting on Cu(111) with a higher energy barrier. On an oxide-derived Cu(100)-dominant Cu catalyst, we reach a high C2H4 Faradaic efficiency of 72%, partial current density of 359 mA cm-2, and long-term stability exceeding 100 h at 500 mA cm-2, greatly outperforming its Cu(111)-rich counterpart. We further demonstrate constant C2H4 selectivity of >60% over 70 h in a membrane electrode assembly electrolyzer with a full-cell energy efficiency of 23.4%.

Bear Bile Powder Ameliorates LPS-Induced Acute Lung Injury by Inhibiting CD14 Pathway and Improving Intestinal Flora: Exploration of "Fei (Lung)-Dachang (Large Intestine) Interaction".

OBJECTIVE: To explore the effect of bear bile powder (BBP) on acute lung injury (ALI) and the underlying mechanism. METHODS: The chemical constituents of BBP were analyzed by ultra-high-pressure liquid chromatography-mass spectrometry (UPLC-MS). After 7 days of adaptive feeding, 50 mice were randomly divided into 5 groups by a random number table (n=10): normal control (NC), lipopolysaccharide (LPS), dexamethasone (Dex), low-, and high-dose BBP groups. The dosing cycle was 9 days. On the 12th and 14th days, 20 µL of Staphylococcus aureus solution (bacterial concentration of 1 × 10-7 CFU/mL) was given by nasal drip after 1 h of intragastric administration, and the mice in the NC group was given the same dose of phosphated buffered saline (PBS) solution. On the 16th day, after 1 h intragastric administration, 100 µL of LPS solution (1 mg/mL) was given by tracheal intubation, and the same dose of PBS solution was given to the NC group. Lung tissue was obtained to measure the myeloperoxidase (MPO) activity, the lung wet/dry weight ratio and expressions of CD14 and other related proteins. The lower lobe of the right lung was obtained for pathological examination. The concentrations of inflammatory cytokines including interleukin (IL)-6, tumour necrosis factor α (TNF-α ) and IL-1ß in the bronchoalveolar lavage fluid (BALF) were detected by enzyme linked immunosorbent assay, and the number of neutrophils was counted. The colonic contents of the mice were analyzed by 16 sRNA technique and the contents of short-chain fatty acids (SCFAs) were measured by gas chromatograph-mass spectrometer (GC-MS). RESULTS: UPLC-MS revealed that the chemical components of BBP samples were mainly tauroursodeoxycholic acid and taurochenodeoxycholic acid sodium salt. BBP reduced the activity of MPO, concentrations of inflammatory cytokines, and inhibited the expression of CD14 protein, thus suppressing the activation of NF-κB pathway (P<0.05). The lung histopathological results indicated that BBP significantly reduced the degree of neutrophil infiltration, cell shedding, necrosis, and alveolar cavity depression. Moreover, BBP effectively regulated the composition of the intestinal microflora and increased the production of SCFAs, which contributed to its treatment effect (P<0.05). CONCLUSIONS: BBP alleviates lung injury in ALI mouse through inhibiting activation of NF-κB pathway and decreasing expression of CD14 protein. BBP may promote recovery of ALI by improving the structure of intestinal flora and enhancing metabolic function of intestinal flora.

Efficient and stable acidic CO2 electrolysis to formic acid by a reservoir structure design.

Electrochemical synthesis of valuable chemicals and feedstocks through carbon dioxide (CO2) reduction in acidic electrolytes can surmount the considerable CO2 loss in alkaline and neutral conditions. However, achieving high productivity, while operating steadily in acidic electrolytes, remains a big challenge owing to the severe competing hydrogen evolution reaction. Here, we show that vertically grown bismuth nanosheets on a gas-diffusion layer can create numerous cavities as electrolyte reservoirs, which confine in situ-generated hydroxide and potassium ions and limit inward proton diffusion, producing locally alkaline environments. Based on this design, we achieve formic acid Faradaic efficiency of 96.3% and partial current density of 471 mA cm-2 at pH 2. When operated in a slim continuous-flow electrolyzer, the system exhibits a full-cell formic acid energy efficiency of 40% and a single pass carbon efficiency of 79% and performs steadily over 50 h. We further demonstrate the production of pure formic acid aqueous solution with a concentration of 4.2 weight %.

Gerhardtite as a Precursor to an Efficient CO-to-Acetate Electroreduction Catalyst.

Carbon-carbon coupling electrochemistry on a conventional copper (Cu) catalyst still undergoes low selectivity among many different multicarbon (C2+) chemicals, posing a grand challenge to achieve a single C2+ product. Here, we demonstrate a laser irradiation synthesis of a gerhardtite mineral, Cu2(OH)3NO3, as a catalyst precursor to make a Cu catalyst with abundant stacking faults under reducing conditions. Such structural perturbation modulates electronic microenvironments of Cu, leading to improved d-electron back-donation to the antibonding orbital of *CO intermediates and thus strengthening *CO adsorption. With increased *CO coverage on the defect-rich Cu, we report an acetate selectivity of 56 ± 2% (compared to 31 ± 1% for conventional Cu) and a partial current density of 222 ± 7 mA per square centimeter in CO electroreduction. When run at 400 mA per square centimeter for 40 h in a flow reactor, this catalyst produces 68.3 mmol of acetate throughout. This work highlights the value of a Cu-containing mineral phase in accessing suitable structures for improved selectivity to a single desired C2+ product.

Efficient acidic hydrogen evolution in proton exchange membrane electrolyzers over a sulfur-doped marcasite-type electrocatalyst.

Large-scale deployment of proton exchange membrane (PEM) water electrolyzers has to overcome a cost barrier resulting from the exclusive adoption of platinum group metal (PGM) catalysts. Ideally, carbon-supported platinum used at cathode should be replaced with PGM-free catalysts, but they often undergo insufficient activity and stability subjecting to corrosive acidic conditions. Inspired by marcasite existed under acidic environments in nature, we report a sulfur doping-driven structural transformation from pyrite-type cobalt diselenide to pure marcasite counterpart. The resultant catalyst drives hydrogen evolution reaction with low overpotential of 67 millivolts at 10 milliamperes per square centimeter and exhibits no degradation after 1000 hours of testing in acid. Moreover, a PEM electrolyzer with this catalyst as cathode runs stably over 410 hours at 1 ampere per square centimeter and 60°C. The marked properties arise from sulfur doping that not only triggers formation of acid-resistant marcasite structure but also tailors electronic states (e.g., work function) for improved hydrogen diffusion and electrocatalysis.

Identification of Cu(100)/Cu(111) Interfaces as Superior Active Sites for CO Dimerization During CO2 Electroreduction.

The electrosynthesis of valuable multicarbon chemicals using carbon dioxide (CO2) as a feedstock has substantially progressed recently but still faces considerable challenges. A major difficulty lines in the sluggish kinetics of forming carbon-carbon (C-C) bonds, especially in neutral media. We report here that oxide-derived copper crystals enclosed by six {100} and eight {111} facets can reduce CO2 to multicarbon products with a high Faradaic efficiency of 74.9 ± 1.7% at a commercially relevant current density of 300 mA cm-2 in 1 M KHCO3 (pH ∼ 8.4). By combining the experimental and computational studies, we uncovered that Cu(100)/Cu(111) interfaces offer a favorable local electronic structure that enhances *CO adsorption and lowers C-C coupling activation energy barriers, performing superior to Cu(100) and Cu(111) surfaces, respectively. On this catalyst, no obvious degradation was observed at 300 mA cm-2 over 50 h of continuous operation.

Stabilizing indium sulfide for CO2 electroreduction to formate at high rate by zinc incorporation.

Recently developed solid-state catalysts can mediate carbon dioxide (CO2) electroreduction to valuable products at high rates and selectivities. However, under commercially relevant current densities of > 200 milliamperes per square centimeter (mA cm-2), catalysts often undergo particle agglomeration, active-phase change, and/or element dissolution, making the long-term operational stability a considerable challenge. Here we report an indium sulfide catalyst that is stabilized by adding zinc in the structure and shows dramatically improved stability. The obtained ZnIn2S4 catalyst can reduce CO2 to formate with 99.3% Faradaic efficiency at 300 mA cm-2 over 60 h of continuous operation without decay. By contrast, similarly synthesized indium sulfide without zinc participation deteriorates quickly under the same conditions. Combining experimental and theoretical studies, we unveil that the introduction of zinc largely enhances the covalency of In-S bonds, which "locks" sulfur-a catalytic site that can activate H2O to react with CO2, yielding HCOO* intermediates-from being dissolved during high-rate electrolysis.

Strongly Coupled Cobalt Diselenide Monolayers for Selective Electrocatalytic Oxygen Reduction to H2 O2 under Acidic Conditions.

Electrosynthesis of hydrogen peroxide (H2 O2 ) in the acidic environment could largely prevent its decomposition to water, but efficient catalysts that constitute entirely earth-abundant elements are lacking. Here we report the experimental demonstration of narrowing the interlayer gap of metallic cobalt diselenide (CoSe2 ), which creates high-performance catalyst to selectively drive two-electron oxygen reduction toward H2 O2 in an acidic electrolyte. The enhancement of the interlayer coupling between CoSe2 atomic layers offers a favorable surface electronic structure that weakens the critical *OOH adsorption, promoting the energetics for H2 O2 production. Consequently, on the strongly coupled CoSe2 catalyst, we achieved Faradaic efficiency of 96.7 %, current density of 50.04 milliamperes per square centimeter, and product rate of 30.60 mg cm-2 h-1 . Moreover, this catalyst shows no sign of degradation when operating at -63 milliamperes per square centimeter over 100 hours.

Hierarchical Copper with Inherent Hydrophobicity Mitigates Electrode Flooding for High-Rate CO2 Electroreduction to Multicarbon Products.

Copper is currently the material with the most promise as catalyst to drive carbon dioxide (CO2) electroreduction to produce value-added multicarbon (C2+) compounds. However, a copper catalyst on a carbon-based gas diffusion layer electrode often has poor stability-especially when performing at high current densities-owing to electrolyte flooding caused by the hydrophobicity decrease of the gas diffusion layer during operation. Here, we report a bioinspired copper catalyst on a gas diffusion layer that mimics the unique hierarchical structuring of Setaria's hydrophobic leaves. This hierarchical copper structure endows the CO2 reduction electrode with sufficient hydrophobicity to build a robust gas-liquid-solid triple-phase boundary, which can not only trap more CO2 close to the active copper surface but also effectively resist electrolyte flooding even under high-rate operation. We consequently achieved a high C2+ production rate of 255 ± 5.7 mA cm-2 with a 64 ± 1.4% faradaic efficiency, as well as outstanding operational stability at 300 mA cm-2 over 45 h in a flow reactor, largely outperforming its wettable copper counterparts.

An Efficient Turing-Type Ag2 Se-CoSe2 Multi-Interfacial Oxygen-Evolving Electrocatalyst*.

Although the Turing structures, or stationary reaction-diffusion patterns, have received increasing attention in biology and chemistry, making such unusual patterns on inorganic solids is fundamentally challenging. We report a simple cation exchange approach to produce Turing-type Ag2 Se on CoSe2 nanobelts relied on diffusion-driven instability. The resultant Turing-type Ag2 Se-CoSe2 material is highly effective to catalyze the oxygen evolution reaction (OER) in alkaline electrolytes with an 84.5 % anodic energy efficiency. Electrochemical measurements show that the intrinsic OER activity correlates linearly with the length of Ag2 Se-CoSe2 interfaces, determining that such Turing-type interfaces are more active sites for OER. Combing X-ray absorption and computational simulations, we ascribe the excellent OER performance to the optimized adsorption energies for critical oxygen-containing intermediates at the unconventional interfaces.

[Research Advances in Structural Characteristics,Identification Methods,and Functions of Telocytes].

Telocytes are novel interstitial cells with a specific structure:the body has an elliptical shape or a triangle shape,with slender and thin protrusions that connect with other cells to form a complex 3D network.This article summarizes the structural characteristics and identification Methods of Telocytes and demonstrates their potential functions as a new target for disease prevention and treatment.

Protecting Copper Oxidation State via Intermediate Confinement for Selective CO2 Electroreduction to C2+ Fuels.

Selective and efficient catalytic conversion of carbon dioxide (CO2) into value-added fuels and feedstocks provides an ideal avenue to high-density renewable energy storage. An impediment to enabling deep CO2 reduction to oxygenates and hydrocarbons (e.g., C2+ compounds) is the difficulty of coupling carbon-carbon bonds efficiently. Copper in the +1 oxidation state has been thought to be active for catalyzing C2+ formation, whereas it is prone to being reduced to Cu0 at cathodic potentials. Here we report that catalysts with nanocavities can confine carbon intermediates formed in situ, which in turn covers the local catalyst surface and thereby stabilizes Cu+ species. Experimental measurements on multihollow cuprous oxide catalyst exhibit a C2+ Faradaic efficiency of 75.2 ± 2.7% at a C2+ partial current density of 267 ± 13 mA cm-2 and a large C2+-to-C1 ratio of ∼7.2. Operando Raman spectra, in conjunction with X-ray absorption studies, confirm that Cu+ species in the as-designed catalyst are well retained during CO2 reduction, which leads to the marked C2+ selectivity at a large conversion rate.

Effectiveness of surgical resection for complicated liver cancer and its influencing factors: A retrospective study.

BACKGROUND: Surgical resection is the preferred method for patients with complex liver cancer. But the tumor is in a special position, the surgery is highly risky, postoperative complications can easily occur, and the prognosis is not ideal. AIM: To investigate the effectiveness of surgical resection for complex liver cancer and its influencing factors. METHODS: Fifty-seven patients who had complicated liver cancer and underwent surgical resection at our hospital from August 2015 to August 2016 were enrolled in this study. All patients were followed for three years, and their postoperative complications, survival, and factors that impacted their survival were analyzed. RESULTS: The total incidence of postoperative complications was 45.61%, and the incidence of pleural effusion was the highest at 28.07%. There were no correlations between the 2-year and 3-year survival rates and sex, age, and HbsAg of the patients (P > 0.05). In terms of pathological parameters, the 2-year and 3-year survival rates were significantly different according to the presence of a tumor capsule, degree of liver cirrhosis, satellite or focal lesions, hepatic vein thrombosis, portal vein tumor thrombus, and intraoperative blood loss (P < 0.05). CONCLUSION: The effectiveness of surgical resection for complex hepatocellular carcinoma may be affected by factors such as the presence of a tumor capsule, cirrhosis degree, satellite or focal lesions, hepatic vein embolization, portal vein tumor thrombus, and intraoperative blood loss. Therefore, these factors should be controlled and prevented during surgery to help improve patient survival after surgery.

Deep learning-based automated detection of retinal diseases using optical coherence tomography images.

Retinal disease classification is a significant problem in computer-aided diagnosis (CAD) for medical applications. This paper is focused on a 4-class classification problem to automatically detect choroidal neovascularization (CNV), diabetic macular edema (DME), DRUSEN, and NORMAL in optical coherence tomography (OCT) images. The proposed classification algorithm adopted an ensemble of four classification model instances to identify retinal OCT images, each of which was based on an improved residual neural network (ResNet50). The experiment followed a patient-level 10-fold cross-validation process, on development retinal OCT image dataset. The proposed approach achieved 0.973 (95% confidence interval [CI], 0.971-0.975) classification accuracy, 0.963 (95% CI, 0.960-0.966) sensitivity, and 0.985 (95% CI, 0.983-0.987) specificity at the B-scan level, achieving a matching or exceeding performance to that of ophthalmologists with significant clinical experience. Other performance measures used in the study were the area under receiver operating characteristic curve (AUC) and kappa value. The observations of the study implied that multi-ResNet50 ensembling was a useful technique when the availability of medical images was limited. In addition, we performed qualitative evaluation of model predictions, and occlusion testing to understand the decision-making process of our model. The paper provided an analytical discussion on misclassification and pathology regions identified by the occlusion testing also. Finally, we explored the effect of the integration of retinal OCT images and medical history data from patients on model performance.