A nomogram for prediction of ERCP success in patients with bile duct leaks: a multicenter study.

BACKGROUND: Bile duct leaks (BDLs) are serious complications that occurs after hepatobiliary surgery and trauma, leading to rapid clinical deterioration. Endoscopic retrograde cholangiopancreatography (ERCP) is the first-line treatment for BDLs, but it is not clear which patients will respond to this therapy and which patients will require additional surgical intervention. The aim of our study was to explore the predictors of successful ERCP for BDLs. METHODS: A retrospective analysis was conducted using data from six centers' databases. All consecutive patients who were clinically confirmed as BDLs were included in the study. Collected data were demographics, disease severity, and ERCP procedure characteristics. Univariate and multivariate analysis were used to select independent predictive factors that affect the outcome of ERCP for BDLs, and a nomogram was established. Calibration and ROC curves were used to evaluate the models. RESULTS: Four hundred and forty-eight consecutive patients were clinically confirmed as BDLs and 347 were excluded. In the 101 patients included patients, clinical success was achieved in 78 patients (77.2%). In logistic multivariable regression, two independent factors were negatively associated with the success of ERCP: SIRS (OR, 0.183; 95% CI 0.039-0.864; P = 0.032) and high-grade leak (OR 0.073; 95% CI 0.010-0.539; P = 0.010). Two independent factors were positively associated with the success of ERCP: leak-bridging drainage (OR 4.792; 95% CI 1.08-21.21; P = 0.039) and cystic duct leak (OR 6.193; 95% CI 1.03-37.17; P = 0.046). The prediction model with these four factors was evaluated using a receiver-operating characteristic (ROC) curve, which demonstrated an area under the curve of 0.9351. The calibration curve showed that the model had good predictive accuracy. CONCLUSION: Leak-bridging drainage and cystic duct leak are positive predictors for the success of ERCP, while SIRS and high-grade leak are negative predictors. This prediction model with nomogram has good predictive ability and practical clinical value, and may be helpful in clinical decision-making and prognostication.

Switchable deep eutectic solvent as green and efficient media for liquid-phase microextraction of phenoxyacetic acid herbicides in water and food matrices.

In this work, a switchable deep eutectic solvent (SDES) based on fatty acid and polyetheramine ion pair was prepared for liquid-phase microextraction (LPME) of phenoxyacetic acid herbicides in drinking water, beverage and honey matrices. The as-synthesized SDES equipped with an interesting characteristic of fast and reversible polarity switching, achieving homogeneous extraction and rapid bi-phase separation simultaneously. Several key parameters affecting the extraction performance were investigated comprehensively by Box-Behnken design. Under the optimal conditions, the method exhibited excellent linearity (15-4000 µg L-1), low detection limits (3-5 µg L-1), desirable precision (RSD < 8.1 %), and satisfactory recovery (72.6-98.7 %). More importantly, the introduction of SDES can simplify the pre-treatment procedure, shorten extraction time (4 min), and avoid the usage of traditional organic solvent during the whole extraction process. In addition, the switching mechanism of SDES was characterized by FT-IR and 1H NMR, and the forming mechanism of SDES was investigated using density-functional theory. The green of the method was estimated using the analytical ecological scale, the analytical green calculator, and the green analytical procedure index. The cytotoxicity of SDES was investigated and the result displayed that toxicity of the SDES was very low with the EC50 > 500 mg/L. Therefore, the proposed method was green and efficient and revealed considerable application prospects for the extraction of trace analytes from complex materials.

An effervescence-assisted switchable deep eutectic solvent based liquid-phase microextraction of triazole fungicides in drinking water and beverage.

A new effervescence-assisted switchable deep eutectic solvent-based liquid phase microextraction (EA-SDES-LPME) combined with HPLC-UV was developed for determination of common triazole fungicides in drinking water and beverages, including myclobutanil, flusilazole, hexaconazole and bitertanol. The alternative extraction solvent was prepared with hexafluoroisopropanol and dipropylamine with the merits of time-saving, easy to collect and cost-effectiveness. The SDES can be reversibly switched between hydrophilic and hydrophobic states by pH adjustment. The homogeneous extraction was achieved under the hydrophilic form of SDES, and the bi-phase separation was obtained easily by adjusting pH value to restore the original hydrophobicity. Moreover, the characterization of SDES was investigated by FTIR and 1H NMR. The main variables affecting extraction efficiency were optimized in detail. Under the optimal conditions, the proposed method shows desirable precision (RSDs less than 18.5%) and acceptable recovery (72.6-95.4%). The lower limits of detection and limits of quantitation were found to be in the range of 1-2 µg L-1 and 5-10 µg L-1, respectively. The formation mechanism of SDES and the extraction mechanism for target analytes were investigated by density functional theory. The proposed methodology was simplicity, sensitive, time-saving and successfully applied to determine triazole fungicides in drinking water and beverages, making it an alternative technique for the analysis of trace analytes with satisfactory sensitivity.

Solution-processable, robust and sustainable cooler via nano-structured engineering.

Passive daytime radiative cooling (PDRC) materials simultaneously featuring aesthetic and safety distinctions demonstrate versatile applications beyond cooling buildings, while the integrated advantages of high strength, morphological reconfigurability, and sustainability remain challenging for the conventional PDRC materials. Herein, we designed a robust, custom-shaped and eco-friendly cooler via a scalable solution-processable strategy, involving the nano-scale assembly of nano cellulose (NC) and inorganic nanoparticle (e.g., ZrO2, SiO2, BaSO4, and hydroxyapatite). The robust cooler shows an interesting "brick-and-mortar" structure, where the NC constructs interwoven framework (as brick structure) and the inorganic nanoparticle uniformly locates in the skeleton (as mortar structure), collectively contributing to high mechanical strength (>80 MPa) and flexibility. In addition, the structural and chemical distinctions enable our cooler to show a high solar reflectance (>96 %) and mid-infrared emissivity (>0.9), demonstrating a sub-ambient average temperature drop of 8.8 °C in long-term outdoor environments. The high-performance cooler with robustness, scalability and environmental friendliness, serves as a competitive participant toward the advanced PDRC materials in our low-carbon society.

Simplified LDPC-assisted CNC algorithm for entropy-loaded discrete multi-tone in a 100G flexible-rate PON.

Passive optical networks (PONs) have been widely used in optical access networks to meet the requirement of the rapidly growing data traffic. However, the optical power budget of the worst optical network unit certainly limits the maximum capacity of PON. In this paper, we demonstrate a flexible-rate PON based on entropy-loaded clipping discrete multi-tone (DMT) for increasing the capacity. Meanwhile, clipping operation and simplified low-density parity-check (LDPC) assisted clipping-noise-cancellation (CNC) algorithm are proposed to improve the performance of DMT in peak-power constrained PON. In the simplified LDPC-assisted CNC algorithm, the iteration number of the sum-product algorithm in the LDPC decoding can be reduced to decrease the computational complexity almost without performance loss. The experimental results show that the simplified CNC algorithm can achieve approximately 1.8dB improvement of the optical receiver sensitivity at the 20% soft-decision forward-error-correction limit. The proposed flexible-rate PON has a wide-range data-rate adjustment from 12.5Gb/s to 100Gb/s under the optical power budget from 40dB to 26dB.

A noble bimetal oxysulfide CuVOS catalyst for highly efficient catalytic reduction of 4-nitrophenol and organic dyes.

A novel copper-vanadium bimetallic oxysulfide (CuVOS) nanoparticle catalyst was successfully synthesized by a facile method. The samples were characterized by X-ray photoelectron spectrometry (XPS), X-ray diffractometry (XRD), field-emission scanning electron microscopy (FE-SEM), UV-Vis diffuse spectroscopy (DRS), Fourier transform infrared spectroscopy (FTIR), and N2 adsorption-desorption isotherms. In order to check the catalytic efficiencies toward reduction reaction, 4-nitrophenol (4-NP) and other organic dyes such as rhodamine-B (RhB), methylene blue (MB), and methyl orange (MO) were used. The results showed that the CuVOS prepared in the presence of a suitable amount of N2H4 during the synthesis of the nanoparticles exhibited the fastest reduction capabilities by using NaBH4 as a reducing agent. It was demonstrated that a 100 mL 4-NP (20 ppm) solution was completely reduced by 5 mg CuVOS-3 within 2 min. Moreover, the complete reduction of 100 mL of MO, RhB, and MB solutions of 100 ppm was also achieved by 5 mg CuVOS-3 within 2 min, 6 min, and 5 min, respectively. Hence, the CuVOS is an efficient catalyst for reducing 4-NP and organic dyes and can have great potential for industrial application.