Furosemide does not reduce the incidence of postoperative acute kidney injury in adult patients undergoing cardiac surgery: A PRISMA-compliant systematic review and meta-analysis.

OBJECTIVE: Acute kidney injury (AKI) is a common complication of cardiac surgical patients, the occurrence of which is multifactorial. Furosemide is the most common loop diuretic and widely used in cardiac surgery to reduce fluid overload, increase tubular flow and urine output. It remains unknown whether furosemide affects the incidence or prognosis of cardiac surgery-induced acute kidney injury (CS-AKI). Therefore, the current study was performed to address this question. METHODS: PubMed, Embase, Scopus, Cochrane Library, and Web of Science databases were searched for relevant studies. Primary outcomes of interest included postoperative CS-AKI incidence, need for renal replacement therapy (RRT) rate. Secondary outcomes of interest included postoperative serum creatinine (Scr) and blood urea nitrogen (BUN) levels, postoperative mechanical ventilation duration (MVD), length of stay (LOS) in intensive care unit (ICU) and in hospital, and mortality. The odds ratio (OR) and/or the weighted mean difference (WMD) with 95% confidence interval (CI) were used to pool the data. RESULTS: Database search yielded six studies including 566 adult patients, and 283 patients were allocated into Group Furosemide and 283 into Group Control (Placebo). Heterogeneity between studies was deemed acceptable, and the publication bias was low. Meta-analysis suggested that furosemide administration in adult cardiac surgical patients had no effect on CS-AKI incidence (n = 4 trials; OR = 0.92; 95% CI: 0.37-2.30; p = .86; I2 = 57%) and need for RRT rate (n = 2 trials; OR = 4.13; 95% CI: 0.44-38.51; p = .21; I2 = 0%). Diversely, furosemide administration in adult cardiac surgical patients significantly decreased postoperative BUN level (n = 3 trials; WMD = 0.71; 95% CI: 0.10-1.33; p = .02; I2 = 0%), postoperative MVD (n = 2 trials; WMD = -3.13; 95% CI: -3.78 to -2.49; p < .00001; I2 = 0%) and postoperative LOS in ICU (n = 3 trials; WMD = -0.47; 95% CI: -0.76 to -0.18; p = .001; I2 = 0%). However, it had no significant impact on postoperative Scr level, postoperative LOS in hospital, and postoperative mortality. CONCLUSION: This meta-analysis suggested that furosemide administration in adult cardiac surgical patients had no significant effect on CS-AKI incidence, need for RRT rate, postoperative Scr level, LOS in hospital and mortality, but could reduce postoperative BUN level, MVD, and LOS in ICU. As only a limited number of studies were included, these results should be interpreted carefully and cautiously. Future high-quality randomized controlled trials are needed to define the role of furosemide in CS-AKI prevention and management.

Nanoparticle-Catalyzed Green Chemistry Synthesis of Polybenzoxazole.

Enabling catalysts to promote multistep chemical reactions in a tandem fashion is an exciting new direction for the green chemistry synthesis of materials. Nanoparticle (NP) catalysts are particularly well suited for tandem reactions due to the diverse surface-active sites they offer. Here, we report that AuPd alloy NPs, especially 3.7 nm Au42Pd58 NPs, catalyze one-pot reactions of formic acid, diisopropoxy-dinitrobenzene, and terephthalaldehyde, yielding a very pure thermoplastic rigid-rod polymer, polybenzoxazole (PBO), with a molecular weight that is tunable from 5.8 to 19.1 kDa. The PBO films are more resistant to hydrolysis and possess thermal and mechanical properties that are superior to those of commercial PBO, Zylon. Cu NPs are also active in catalyzing tandem reactions to form PBO when formic acid is replaced with ammonia borane. Our work demonstrates a general approach to the green chemistry synthesis of rigid-rod polymers as lightweight structural materials for broad thermomechanical applications.

A New Hexagonal Cobalt Nanosheet Catalyst for Selective CO2 Conversion to Ethanal.

We report a new form of catalyst based on ferromagnetic hexagonal-close-packed (hcp) Co nanosheets (NSs) for selective CO2RR to ethanal, CH3CHO. In all reduction potentials tested from -0.2 to -1.0 V (vs RHE) in 0.5 M KHCO3 solution, the reduction yields ethanal as a major product and ethanol/methanol as minor products. At -0.4 V, the Faradaic efficiency (FE) for ethanal reaches 60% with current densities of 5.1 mA cm-2 and mass activity of 3.4 A g-1 (total FE for ethanal/ethanol/methanol is 82%). Density functional theory (DFT) calculations suggest that this high CO2RR selectivity to ethanal on the hcp Co surface is attributed to the unique intralayer electron transfer, which not only promotes [OC-CO]* coupling but also suppresses the complete hydrogenation of the coupling intermediates to ethylene, leading to highly selective formation of CH3CHO.

Stabilizing Hard Magnetic SmCo5 Nanoparticles by N-Doped Graphitic Carbon Layer.

We report a chemical method to synthesize size-controllable SmCo5 nanoparticles (NPs) and to stabilize the NPs against air oxidation by coating a layer of N-doped graphitic carbon (NGC). First 10 nm CoO and 5 nm Sm2O3 NPs were synthesized and aggregated in reverse micelles of oleylamine to form SmCo-oxide NPs with a controlled size (110, 150, or 200 nm). The SmCo-O NPs were then coated with polydopamine and thermally annealed to form SmCo-O/NGC NPs, which were further embedded in CaO matrix and reduced with Ca at 850 °C to give SmCo5/NGC NPs of 80, 120, or 180 nm, respectively. The 10 nm NGC coating efficiently stabilized the SmCo5 NPs against air oxidation at room temperature or at 100 °C. The magnetization value of the 180 nm SmCo5/NGC NPs was stabilized at 86.1 emu/g 5 days after air exposure at room temperature and dropped only 1.7% 48 h after air exposure at 100 °C. The stable SmCo5/NGC NPs were aligned magnetically in an epoxy resin, showing a square-like hysteresis behavior with their Hc reaching 51.1 kOe at 150 K and 21.9 kOe at 330 K and their Mr stabilized at around 84.8 emu/g. Our study demonstrates a new strategy for synthesizing and stabilizing SmCo5 NPs for high-performance nanomagnet applications in a broad temperature range.

Anisotropic Strain Tuning of L10 Ternary Nanoparticles for Oxygen Reduction.

Tuning the performance of nanoparticle (NP) catalysts by controlling the NP surface strain has evolved as an important strategy to optimize NP catalysis in many energy conversion reactions. Here, we present our new study on using an eigenforce model to predict and experiments to verify the strain-induced catalysis enhancement of the oxygen reduction reaction (ORR) in the presence of L10-CoMPt NPs (M = Mn, Fe, Ni, Cu, Ni). The eigenforce model allowed us to predict anisotropic (that is, two-dimensional) strain levels on distorted Pt(111) surfaces. Experimentally, by preparing a series of 5 nm L10-CoMPt NPs, we could push the ORR catalytic activity of these NPs toward the optimum region of the theoretical two-dimensional volcano plot predicted for L10-CoMPt. The best ORR catalyst in the alloy NP series we studied is L10-CoNiPt, which has a mass activity of 3.1 A/mgPt and a specific activity of 9.3 mA/cm2 at room temperature with only 15.9% loss of mass activity after 30 000 cycles at 60 °C in 0.1 M HClO4.

Virtual optics and sensing of the retrieved complex field in the back focal plane using a constrained defocus algorithm.

The reflected back focal plane from a microscope objective is known to provide excellent information of material properties and can be used to analyze the generation of surface plasmons and surface waves in a localized region. Most analysis has concentrated on direct measurement of the reflected intensity in the back focal plane. By accessing the phase information, we show that examination in the back focal plane becomes considerably more powerful allowing the reconstructed field to be filtered, propagated and analyzed in different domains. Moreover, the phase often gives a superior measurement that is far easier to use in the assessment of the sample, an example of such cases is examined in the present paper. We discuss how the modified defocus phase retrieval algorithm has the potential for real time measurements with parallel image acquisition since only three images are needed for reliable retrieval of arbitrary distributions.

Cu3N Nanocubes for Selective Electrochemical Reduction of CO2 to Ethylene.

Understanding the Cu-catalyzed electrochemical CO2 reduction reaction (CO2RR) under ambient conditions is both fundamentally interesting and technologically important for selective CO2RR to hydrocarbons. Current Cu catalysts studied for the CO2RR can show high activity but tend to yield a mixture of different hydrocarbons, posing a serious challenge on using any of these catalysts for selective CO2RR. Here, we report a new perovskite-type copper(I) nitride (Cu3N) nanocube (NC) catalyst for selective CO2RR. The 25 nm Cu3N NCs show high CO2RR selectivity and stability to ethylene (C2H4) at -1.6 V (vs reversible hydrogen electrode (RHE)) with the Faradaic efficiency of 60%, mass activity of 34 A/g, and C2H4/CH4 molar ratio of >2000. More detailed electrochemical characterization, X-ray photon spectroscopy, and density functional theory calculations suggest that the high CO2RR selectivity is likely a result of (100) Cu(I) stabilization by the Cu3N structure, which favors CO-CHO coupling on the (100) Cu3N surface, leading to selective formation of C2H4. Our study presents a good example of utilizing metal nitrides as highly efficient nanocatalysts for selective CO2RR to hydrocarbons that will be important for sustainable chemistry/energy applications.

CuPd Nanoparticles as a Robust Catalyst for Electrochemical Allylic Alkylation.

An efficient CuPd nanoparticle (NP) catalyst (3 nm CuPd NPs deposited on carbon support) is designed for catalyzing electrochemical allylic alkylation in water/isopropanol (1:1 v/v) and 0.2 m KHCO3 solution at room temperature. The Pd catalysis was Pd/Cu composition-dependent, and CuPd NPs with a Pd/Cu ratio close to one are the most efficient catalyst for the selective cross-coupling of alkyl halides and allylic halides to form C-C hydrocarbons with product yields reaching up to 99 %. This NP-catalyzed electrochemical allylic alkylation expands the synthetic scope of cross-coupling reactions and can be further extended to other organic reaction systems for developing green chemistry electrosynthesis methods.

MOF-Derived CuS@Cu-BTC Composites as High-Performance Anodes for Lithium-Ion Batteries.

The CuS(x wt%)@Cu-BTC (BTC = 1,3,5-benzenetricarboxylate; x = 3, 10, 33, 58, 70, 99.9) materials are synthesized by a facile sulfidation reaction. The composites are composed of octahedral Cu3 (BTC)2 ·(H2 O)3 (Cu-BTC) with a large specific surface area and CuS with a high conductivity. The as-prepared CuS@Cu-BTC products are first applied as the anodes of lithium-ion batteries (LIBs). The synergistic effect between Cu-BTC and CuS components can not only accommodate the volume change and stress relaxation of electrodes but also facilitate the fast transport of Li ions. Thus, it can greatly suppress the transformation process from Li2 S to polysulfides by improving the reversibility of the conversion reaction. Benefiting from the unique structural features, the optimal CuS(70 wt%)@Cu-BTC sample exhibits a remarkably improved electrochemical performance, showing an over-theoretical capacity up to 1609 mAh g-1 after 200 cycles (100 mA g-1 ) with an excellent rate-capability of ≈490 mAh g-1 at 1000 mA g-1 . The outstanding LIB properties indicate that the CuS(70 wt%)@Cu-BTC sample is a highly desirable electrode material candidate for high-performance LIBs.

Identification of waveguide mode and surface plasmon resonance mode using Fourier cross-correlation analysis.

The light reflected into the back focal plane of a microscope objective allows one to gather a great deal of information about the resonant modes excited on a sample. These dips represent modes excited on the sample, which are related to both the material properties and the structure. Automatic identification of these resonances is a vital stage in developing automated machine-learning techniques for high-throughput sample characterization. In previous work, identification of a single isolated mode was demonstrated; here we show how multiple modes can be separately identified using an automated centering procedure in a process we call radial thresholding. Once the center was determined, the radial thresholding process was modified and combined with interpolation to locate the precise modal positions. We show that this method is capable of resolving very closely spaced modes and is sensitive to nanometric changes in sample dimensions. The processing time for the method is sufficiently fast to ensure that it is suited for rapid sample identification.

Room-Temperature Chemoselective Reduction of 3-Nitrostyrene to 3-Vinylaniline by Ammonia Borane over Cu Nanoparticles.

We report a new strategy of controlling catalytic activity and selectivity of Cu nanoparticles (NPs) for the ammonia borane initiated hydrogenation reaction. Cu NPs are active and selective for chemoselective reduction of nitrostyrene to vinylaniline under ambient conditions. Their activity, selectivity, and more importantly, stability are greatly enhanced by their anchoring on WO2.72 nanorods, providing a room-temperature full conversion of nitrostyrene selectively to vinylaniline (>99% yield). Compared with all other catalysts developed thus far, our new Cu/WO2.72 catalyst shows much enhanced hydrogenation selectivity and stability without the use of pressured hydrogen. The synthetic approach demonstrated here can be extended to prepare various M/WO2.72 catalysts (M = Fe, Co, Ni), with M being stabilized for many chemical reactions.

Adjustable microscopic measurement of nanogap waveguide and plasmonic structures.

We investigate the performance of surface plasmon and Fabry-Perot modes formed between two closely spaced layers. The motivation for this study is twofold: first, to look for modes that may be excited at lower incident angles compared to the usual Kretschmann configuration with similar or superior refractive index responsivity and, second, to develop a simple and applicable method to study these structures over a wide range of separations without recourse to the construction of ad hoc structures. Using back focal plane observation and appropriate signal processing, we show results for the Otto configuration at visible wavelengths at a range of separations not reported hitherto. Moreover, we investigate a hybrid structure we call the Kretschmann-Otto configuration that gives modes that change continuously from a hybridized surface plasmon mode to a zero-order Fabry-Perot mode. The ability to change the separation to small gap distances enables us to examine the Fabry-Perot modes where we show that it has superior refractive index responsivity, by more than an order of magnitude, compared to the Kretschmann configuration.

Maximizing the Catalytic Activity of Nanoparticles through Monolayer Assembly on Nitrogen-Doped Graphene.

We report a facile method for assembly of a monolayer array of nitrogen-doped graphene (NG) and nanoparticles (NPs) and the subsequent transfer of two layers onto a solid substrate (S). Using 3 nm NiPd NPs as an example, we demonstrate that NiPd-NG-Si (Si=silicon wafer) can function as a catalyst and show maximum NiPd catalysis for the hydrolysis of ammonia borane (H3 NBH3 , AB) with a turnover frequency (TOF) of 4896.8 h-1 and an activation energy (Ea ) of 18.8 kJ mol-1 . The NiPd-NG-S catalyst is also highly active for catalyzing the transfer hydrogenation from AB to nitro compounds, leading to the green synthesis of quinazolines in water. Our assembly method can be extended to other graphene and NP catalyst materials, providing a new 2D NP catalyst platform for catalyzing multiple reactions in one pot with maximum efficiency.

STM analysis of surface-adsorbed conjugated oligo(p-phenylene-ethynylene) (OPE) nanostructures.

The nanostructures of a series of conjugated oligo(p-phenylene-ethynylene)s (OPE) adsorbed on a surface were thoroughly studied using scanning tunneling microscopy (STM). These oligomers have different backbone lengths and side chains. As a result, various nanostructures displaying periodic linear patterns at a single molecule level were obtained. Based on careful measurements on the STM images in combination with density functional theory (DFT) calculations, it could be found that the vertical and parallel distances between neighboring oligomers were responsible for the specific arrangement of the backbone and side chains. The results showed that these molecular designs strongly affect their self-assembled structure, which is important to clarify the structure-property relationship in the nanoscience field.

No Genetic Causality between Tobacco Smoking and Venous Thromboembolism: A Two-Sample Mendelian Randomization Study.

BACKGROUND: Given the current debate in clinical research about the relationship between tobacco smoking and the risk of venous thromboembolism (VTE), a Mendelian randomization (MR) study was conducted aimed at elucidating the causal associations of current and past tobacco smoking with the risk of VTE, from the perspective of genetics. METHODS: Two-sample univariate and multivariable MR analyses were designed, using summary-level data from large genome-wide association studies involving European individuals. Causality was primarily assessed using multiplicative fixed-effects or random-effects model and inverse variance weighting, supplemented by MR-Egger regression, MR-PRESSO, Cochran's Q test, and leave-one-out for sensitivity analysis to test the reliability of the results. RESULTS: In the univariate MR analysis, no significant causal effects were found between current tobacco smoking and the risk of VTE, deep vein thrombosis (DVT), and pulmonary embolism (PE). Similarly, no significant causal effects were found between past smoking and VTE, DVT, and PE. As for the multivariable MR analysis, results were consistent with univariate MR analysis, with no significant causal effect of either current or past tobacco smoking on the risk of VTE, DVT, and PE. CONCLUSION: Evidence from both univariate and multivariable MR analyses demonstrated no significant causal relationships between current and past tobacco smoking and VTE, DVT, and PE. This contradicts positive correlations reported in some previous observational studies, which may be explained by other confounding factors. This provided genetic evidence for the conclusion reported in other observational studies that smoking did not affect VTE risk.

Enabling Pd Catalytic Selectivity via Engineering Intermetallic Core@Shell Structure.

Core@shell nanoparticles (NPs) have been widely explored to enhance catalysis due to the synergistic effects introduced by their nanoscale interface and surface structures. However, creating a catalytically functional core@shell structure is often a synthetic challenge due to the need to control the shell thickness. Here, we report a one-step synthetic approach to core-shell CuPd@Pd NPs with an intermetallic B2-CuPd core and a thin (∼0.6 nm) Pd shell. This core@shell structure shows enhanced activity toward selective hydrogenation of Ar-NO2 and allows one-pot tandem hydrogenation of Ar-NO2 to Ar-NH2 and its condensation with Ar-CHO to form Ar-N═CH-Ar. DFT calculations indicate that the B2-CuPd core promotes the Pd shell binding to Ar-NO2 more strongly than to Ar-CHO, thereby selectively activating Ar-NO2. The chemoselective catalysis demonstrated by B2-CuPd@Pd can be extended to a broader scope of substrates, allowing green chemistry synthesis of a wide range of functional chemicals and materials.

Production of Margarine Fat Containing Medium- and Long-Chain Triacylglycerols by Enzymatic Interesterification of Peony Seed Oil, Palm Stearin and Coconut Oil Blends.

This paper reports the preparation of margarine fat using Lipozyme TL IM as a catalyst and peony seed oil (PSO), palm stearin (PS) and coconut oil (CO) as raw materials. The results indicate that there were no significant changes in fatty acid composition before or after interesterification of the oil samples. However, the total amount of medium- and long-chain triglycerides (MLCTs) increased from 2.92% to 11.38% in sample E1 after interesterification, mainly including LaLaO, LaMO, LaPM, LaOO, LaPO and LaPP. Moreover, the slip melting point (SMP) of sample E1 decreased from 45.9 °C (B1) to 33.5 °C. The solid fat content (SFC) of all the samples at 20 °C was greater than 10%, indicating that they could effectively prevent oil exudation. After interesterification, the samples exhibited a ß' crystal form and could be used to prepare functional margarine.

An Indoor Fall Monitoring System: Robust, Multistatic Radar Sensing and Explainable, Feature-Resonated Deep Neural Network.

Indoor fall monitoring is challenging for community-dwelling older adults due to the need for high accuracy and privacy concerns. Doppler radar is promising, given its low cost and contactless sensing mechanism. However, the line-of-sight restriction limits the application of radar sensing in practice, as the Doppler signature will vary when the sensing angle changes, and signal strength will be substantially degraded with large aspect angles. Additionally, the similarity of the Doppler signatures among different fall types makes it extremely challenging for classification. To address these problems, in this paper we first present a comprehensive experimental study to obtain Doppler radar signals under large and arbitrary aspect angles for diverse types of simulated falls and daily living activities. We then develop a novel, explainable, multi-stream, feature-resonated neural network (eMSFRNet) that achieves fall detection and a pioneering study of classifying seven fall types. eMSFRNet is robust to both radar sensing angles and subjects. It is also the first method that can resonate and enhance feature information from noisy/weak Doppler signatures. The multiple feature extractors - including partial pre-trained layers from ResNet, DenseNet, and VGGNet - extracts diverse feature information with various spatial abstractions from a pair of Doppler signals. The feature-resonated-fusion design translates the multi-stream features to a single salient feature that is critical to fall detection and classification. eMSFRNet achieved 99.3% accuracy detecting falls and 76.8% accuracy for classifying seven fall types. Our work is the first effective multistatic robust sensing system that overcomes the challenges associated with Doppler signatures under large and arbitrary aspect angles, via our comprehensible feature-resonated deep neural network. Our work also demonstrates the potential to accommodate different radar monitoring tasks that demand precise and robust sensing.

Apolipoprotein E is required for brain iron homeostasis in mice.

BACKGROUND: Apolipoprotein E deficiency (ApoE-/-) increases progressively iron in the liver, spleen and aortic tissues with age in mice. However, it is unknown whether ApoE affects brain iron. METHODS: We investigated iron contents, expression of transferrin receptor 1 (TfR1), ferroportin 1 (Fpn1), iron regulatory proteins (IRPs), aconitase, hepcidin, Aß42, MAP2, reactive oxygen species (ROS), cytokines and glutathione peroxidase 4 (Gpx4) in the brain of ApoE-/- mice. RESULTS: We demonstrated that ApoE-/- induced a significant increase in iron, TfR1 and IRPs and a reduction in Fpn1, aconitase and hepcidin in the hippocampus and basal ganglia. We also showed that replenishment of ApoE absent partly reversed the iron-related phenotype in ApoE-/- mice at 24-months old. In addition, ApoE-/- induced a significant increase in Aß42, MDA, 8-isoprostane, IL-1ß, IL-6, and TNFα and a reduction in MAP2 and Gpx4 in hippocampus, basal ganglia and/or cortex of mice at 24-months old. CONCLUSIONS: Our findings implied that ApoE is required for brain iron homeostasis and ApoE-/--induced increase in brain iron is due to the increased IRP/TfR1-mediated cell-iron uptake as well as the reduced IRP/Fpn1 associated cell-iron export and suggested that ApoE-/- induced neuronal injury resulted mainly from the increased iron and subsequently ROS, inflammation and ferroptosis.

A total-internal-reflection-based Fabry-Pérot resonator for ultra-sensitive wideband ultrasound and photoacoustic applications.

In photoacoustic and ultrasound imaging, optical transducers offer a unique potential to provide higher responsivity, wider bandwidths, and greatly reduced electrical and acoustic impedance mismatch when compared with piezoelectric transducers. In this paper, we propose a total-internal-reflection-based Fabry-Pérot resonator composed of a 12-nm-thick gold layer and a dielectric resonant cavity. The resonator uses the same Kretschmann configuration as surface plasmon resonators (SPR). The resonators were analyzed both theoretically and experimentally. The experimental results were compared with those for an SPR for benchmarking. The 1.9-µm-thick-PMMA- and 3.4-µm-thick-PDMS-based resonators demonstrated responsivities of 3.6- and 30-fold improvements compared with the SPR, respectively. The measured bandwidths for the PMMA, PDMS devices are 110 MHz and 75 MHz, respectively. Single-shot sensitivity of 160 Pa is obtained for the PDMS device. The results indicate that, with the proposed resonator in imaging applications, sensitivity and the signal-to-noise ratio can be improved significantly without compromising the bandwidth.