Serum uric acid could be served as an independent marker for increased risk and severity of ascending aortic dilatation in Behçet's disease patients.

OBJECTIVE: This study aimed to investigate the correlation of serum uric acid (SUA) with risk and dilatation diameter of ascending aortic dilatation (AAD) in Behçet's disease (BD) patients. METHODS: Seventeen BD patients complicated with AAD and 20 BD patients without AAD were consecutively enrolled and categorized into AAD group and control group, respectively. Ascending aortic dilatation was determined by two-dimensional doppler echocardiographic examination, and AAD was defined as a diameter of ascending aorta ≥3.8 and <4.4 cm. SUA was detected by quantitative immunoassay method. RESULTS: Ascending aortic dilatation patients presented with higher proportion of male patients (P = 0.003), hypertension occurrence (P = 0.036) and increased diameter of ascending aorta (P < 0.001) compared to controls. SUA was elevated in AAD patients compared to controls (P = 0.002), and receiver operating characteristic curve displayed that SUA presented with great predictive value for AAD risk in BD patients with area under curve (AUC) 0.821 (95% CI 0.675-0.966). Pearson's analysis also disclosed that SUA was positively correlated with ascending aortic diameter in total BD patients. However, no difference of CRP (P = 0.219) or ESR (P = 0.320) between AAD patients and controls was observed, and no correlation of CRP (R = -0.150, P = 0.377) or ESR (R = 0.067, P = 0.692) with ascending aortic diameter in total BD patients was discovered either. Further multivariate logistic regression illuminated that SUA was an independent factor predicting AAD risk in BD patients (P = 0.031). CONCLUSIONS: Serum uric acid could be served as an independent marker for increased risk and severity of AAD in BD patients.

The potential for machine learning in hybrid QM/MM calculations.

Hybrid quantum-mechanics/molecular-mechanics (QM/MM) simulations are popular tools for the simulation of extended atomistic systems, in which the atoms in a core region of interest are treated with a QM calculator and the surrounding atoms are treated with an empirical potential. Recently, a number of atomistic machine-learning (ML) tools have emerged that provide functional forms capable of reproducing the output of more expensive electronic-structure calculations; such ML tools are intriguing candidates for the MM calculator in QM/MM schemes. Here, we suggest that these ML potentials provide several natural advantages when employed in such a scheme. In particular, they may allow for newer, simpler QM/MM frameworks while also avoiding the need for extensive training sets to produce the ML potential. The drawbacks of employing ML potentials in QM/MM schemes are also outlined, which are primarily based on the added complexity to the algorithm of training and re-training ML models. Finally, two simple illustrative examples are provided which show the power of adding a retraining step to such "QM/ML" algorithms.

Oxygen-induced changes to selectivity-determining steps in electrocatalytic CO2 reduction.

The state of the electrocatalyst surface-including the oxidation state of the catalyst and the presence of spectator species-is investigated on Cu surfaces with density functional theory in order to understand predicted ramifications on the selectivity and efficiency of CO2 reduction. We examined the presence of oxygen-based species, including the fully oxidized Cu2O surface, the partially oxidized Cu(110)-(2 × 1)O surface, and the presence of OH spectators. The relative oxygen binding strength among these surfaces can help to explain the experimentally observed selectivity change between CH4 and CH3OH on these electrodes; this suggests that the oxygen-binding strength may be a key parameter which predicts the thermodynamically preferred selectivity for pathways proceeding through a methoxy (CH3O) intermediate. This study shows the importance of the local surface environment in the product selectivity of electrocatalysis, and suggests a simple descriptor that can aid in the design of improved electrocatalytic materials.

Active and selective conversion of CO2 to CO on ultrathin Au nanowires.

In this communication, we show that ultrathin Au nanowires (NWs) with dominant edge sites on their surface are active and selective for electrochemical reduction of CO2 to CO. We first develop a facile seed-mediated growth method to synthesize these ultrathin (2 nm wide) Au NWs in high yield (95%) by reducing HAuCl4 in the presence of 2 nm Au nanoparticles (NPs). These NWs catalyze CO2 reduction to CO in aqueous 0.5 M KHCO3 at an onset potential of -0.2 V (vs reversible hydrogen electrode). At -0.35 V, the reduction Faradaic efficiency (FE) reaches 94% (mass activity 1.84 A/g Au) and stays at this level for 6 h without any noticeable activity change. Density functional theory (DFT) calculations suggest that the excellent catalytic performance of these Au NWs is attributed both to their high mass density of reactive edge sites (≥16%) and to the weak CO binding on these sites. These ultrathin Au NWs are the most efficient nanocatalyst ever reported for electrochemical reduction of CO2 to CO.

Faster nucleation at lower pH: amorphous phase mediated nucleation kinetics.

Faster nucleation of hydroxyapatite (HAP) at lower pH (with lower supersaturation) contradicts classical understanding. We find that the residue calcium ion in the mother liquor is the key to trigger ACP phase transformation, which gives an understanding of nonclassical nucleation kinetics of ACP-mediated crystallization and sheds light on biomineralization.

Changes of left atrial morphology and function evaluated with four-dimensional automated left atrial quantification echocardiography in patients with coronary slow flow phenomenon and preserved left ventricular ejection fraction.

BACKGROUND: Coronary slow flow phenomenon (CSFP) can cause left ventricular diastolic dysfunction (LVDD). In multiple studies, the left atrial (LA) strain has been reported to be an excellent parameter for assessing LVDD. The 4-dimensional automated LA quantification (4D Auto LAQ) dedicated to the LA was recently available. Our study aimed to evaluate subclinical changes in LA morphology and function with 4D Auto LAQ in patients with CSFP and preserved left ventricular ejection fraction (LVEF). METHODS: Forty-eight patients with CSFP confirmed with coronary angiography and 46 age and gender-matched controls with normal coronary flow were enrolled. The thrombolysis in myocardial infarction frame count (TFC) method was used to record coronary blood flow velocities for each major coronary artery. LA volume, LA longitudinal and circumferential strains during each of the three LA phases (reservoir, conduit, and contraction), LA total emptying fraction (LATEF), LA active emptying fraction (LAAEF), and LA passive emptying fraction (LAPEF) were quantified with 4D Auto LAQ analysis. RESULTS: Compared with controls, LA longitudinal reservoir strain (LASr), LA longitudinal strain during the conduit phase (LAScd), LA contraction strain (LASct), LA conduit circumferential strain (LAScd-c), LATEF, LAPEF decreased significantly in individuals with CSFP. Of the 4D- LAQ parameters, only LASr [odds ratio (OR): 0.773, P < 0.001] and LATEF [OR: 0.762, P < 0.001] were associated with CSFP in multivariate analysis. A LASr ≤23.00% can differentiate CSFP from controls [sensitivity, 66.7%; specificity, 93.5%; area under the curve (AUC), 0.823; P < 0.001]. A LASr of ≤19.00% could predict the elevation of LV filling pressure in the CSFP cohort [sensitivity, 76.9%; specificity, 74.3%; area under the curve (AUC), 0.792; P < 0.001]. LASr was the only index to demonstrate significant changes compared to controls in single-vessel CSFP. Compared to the right coronary artery (RCA) and left circumflex (LCX), TFC of the left anterior descending (LAD) artery was the only independent variable of LASr (Standardized Coefficients: -0.386, P = 0.037). CONCLUSIONS: Impairment of LA reservoir function reflected by changes in LASr and LATEF can be seen in patients with CSFP. LASr could predict the elevation of LV filling pressure in CSFP individuals. LASr is more sensitive than LATEF in detecting LA reservoir dysfunction in single-vessel CSFP. CSFP in LAD exerts a more prominent influence on LASr than RCA or LCX.

Chinese diabetes datasets for data-driven machine learning.

Data of the diabetes mellitus patients is essential in the study of diabetes management, especially when employing the data-driven machine learning methods into the management. To promote and facilitate the research in diabetes management, we have developed the ShanghaiT1DM and ShanghaiT2DM Datasets and made them publicly available for research purposes. This paper describes the datasets, which was acquired on Type 1 (n = 12) and Type 2 (n = 100) diabetic patients in Shanghai, China. The acquisition has been made in real-life conditions. The datasets contain the clinical characteristics, laboratory measurements and medications of the patients. Moreover, the continuous glucose monitoring readings with 3 to 14 days as a period together with the daily dietary information are also provided. The datasets can contribute to the development of data-driven algorithms/models and diabetes monitoring/managing technologies.

A comparative study of contrast-enhanced ultrasound and contrast-enhanced CT for the detection and characterization of renal masses.

This study aims to compare the value of contrast-enhanced ultrasound (CEUS) and contrast-enhanced CT (CECT) in the differential diagnosis of benign and malignant renal masses. Included in this retrospective study were 143 renal masses in 141 patients using histopathological findings as the gold standard. A comparison was made of the two modalities in image characteristics for their accuracy in the differential diagnosis of renal masses. CEUS and CECT were both used for 39 masses in 37 patients, with 31 (79.5%) being malignant and 8 (20.5%) benign. The differences between the benign and malignant groups in perfusion intensity, perfusion uniformity and entry and exit of the contrast agent were not statistically significant (P > 0.05). However, CEUS could better display the circular perfusion of renal cell carcinoma than CECT (P < 0.05). CECT alone detected 109 masses in 107 patients, with 93 (85.3%) being malignant and 16 (14.7%) benign. CEUS detected 73 masses in 71 patients, with 56 (76.7%) being malignant and 17 (23.3%) benign. No statistically significant differences were observed between CEUS and CECT in the diagnosis of renal cell carcinoma (92.8% vs. 90.3%), with a specificity of 52.9% vs. 31.2%, an accuracy of 83.5% vs. 81.6%, and a positive predictive value of 86.7% vs. 88.4% or a negative predictive value of 69.2% vs. 35.7% (P > 0.05 for all). These results suggested both CEUS and CECT are highly valuable in the differential diagnosis of renal masses, and CEUS can be used as an important supplement for CECT in diagnosis of renal cancer.

Surface Architecture Design of LiNi0.8 Co0.15 Al0.05 O2 Cathode with Synergistic Organics Encapsulation to Enhance Electrochemical Stability.

Ni-rich LiNi0.8 Co0.15 Al0.05 O2 (NCA) material attracts extensive attention due to its high discharge specific capacity, but its distinct drawbacks of rapid capacity decline and poor cycle performance at elevated temperatures and high voltage during charge/discharge cycling restricts its widespread application. To solve these problems, a multifunctional coating layer composed of a lithium-ion-conductive lithium polyacrylate (LiPAA) inner layer and a cross-linked polymer outer layer from certain organic substances of silane-coupling agent (KH550) and polyacrylic acid (PAA) is successfully designed on the surface of NCA materials, which is favorable for eliminating residual lithium and improving lithium-ion conductivity, surface stability, and hydrophobicity of NCA materials. In addition, the amount of the coating material is also investigated. A series of characterization methods such as XRD, FTIR, SEM, TEM, and X-ray photoelectron spectroscopy are used to analyze the morphologies and structures for materials of pristine and modified NCA. It is revealed that the co-coating layer plays a vital part in reducing the surface residual alkalis and improving the stability of NCA particles; as a result, the modified NCA exhibits a greatly improved rate capability, cycle performance, and low polarization impedance.

Cu nanowire-catalyzed electrochemical reduction of CO or CO2.

We prepared micrometer long Cu nanowires (NWs) of 25 and 50 nm diameters and studied their electrocatalysis for electrochemical reduction of CO/CO2 in 0.1 M KHCO3 at room temperature. The 50 nm NWs showed better selectivity than the 25 nm NWs, and catalyzed CO reduction to C2-hydrocarbons (C2H4 + C2H6) with a combined faradaic efficiency (FE) of 60% (C2H4 FE of 35% and mass activity of 4.25 A g-1 Cu) at -1.1 V (vs. reversible hydrogen electrode). The NW-catalyzed CO2 reduction is less efficient due to the extra CO2 to CO step required for the formation of C2-hydrocarbons. This experimental evidence combined with DFT calculations suggests that CO is an important intermediate and NWs provide a large Cu(100) surface for *CO hydrogenation (to *CHO) and *CO-*CHO coupling, leading to more selective reduction of CO than CO2 towards C2-hydrocarbons.

Oxidation suppression during hydrothermal phase reversion allows synthesis of monolayer semiconducting MoS2 in stable aqueous suspension.

This letter demonstrates a simple method to achieve high-yields of 1H semiconducting MoS2 monolayers in concentrated, colloidally-stable aqueous suspension. The method is based on oxidation suppression during the hydrothermal processing step used for metal-to-semiconductor phase reversion. Accompanying DFT calculations on elementary steps in the MoS2 wet oxidation reaction suggest that a two-site corrosion mechanism is responsible for the observed high reactivity and low stability of 1T metallic MoS2.