Ammonium chloride salting out extraction/cleanup for trace-level quantitative analysis in food and biological matrices by flow injection tandem mass spectrometry

A sample extraction and purification procedure that uses ammonium-salt-induced acetonitrile/water phase separation was developed and demonstrated to be compatible with the recently reported method for pesticide residue analysis based on fast extraction and dilution flow injection mass spectrometry (FED-FI-MS). The ammonium salts evaluated were chloride, acetate, formate, carbonate, and sulfate. A mixture of NaCl and MgSO₄, salts used in the well-known QuEChERS method, was also tested for comparison. With thermal decomposition/evaporation temperature of <350 °C, ammonium salts resulted in negligible ion source residual under typical electrospray conditions, leading to consistent method performance and less instrument cleaning. Although all ammonium salts tested induced acetonitrile/water phase separation, NH₄Cl yielded the best performance, thus it was the preferred salting out agent. The NH₄Cl salting out method was successfully coupled with FI/MS/MS and tested for fourteen pesticide active ingredients: chlorantraniliprole, cyantraniliprole, chlorimuron ethyl, oxamyl, methomyl, sulfometuron methyl, chlorsulfuron, triflusulfuron methyl, azimsulfuron, flupyrsulfuron methyl, aminocyclopyrachlor, aminocyclopyrachlor methyl, diuron and hexazinone. A validation study was conducted with nine complex matrices: sorghum, rice, grapefruit, canola, milk, eggs, beef, urine and blood plasma. The method is applicable to all analytes, except aminocyclopyrachlor. The method was deemed appropriate for quantitative analysis in 114 out of 126 analyte/matrix cases tested (applicability rate = 0.90). The NH₄Cl salting out extraction/cleanup allowed expansion of FI/MS/MS for analysis in food of plant and animal origin, and body fluids with increased ruggedness and sensitivity, while maintaining high-throughput (run time = 30 s/sample). Limits of quantitation (LOQs) of 0.01 mg kg⁻¹ (ppm), the ‘well-accepted standard’ in pesticide residue analysis, were achieved in >80% of cases tested; while limits of detection (LODs) were typically in the range of 0.001–0.01 mg kg⁻¹ (ppm). A comparison to a well-established HPLC/MS/MS method was also conducted, yielding comparable results, thus confirming the suitability of NH₄Cl salting out FI/MS/MS for pesticide residue analysis.     

Non-linear parallel solver for detecting point sources in CMB maps using Bayesian techniques

In this work we present a suitable computational tool to deal with large matrices and solve systems of non-linear equations. This technique is applied to a very interesting problem: the detection and flux estimation of point sources in Cosmic Microwave Background (CMB) maps, which allows a good determination of CMB primordial fluctuations and leads to a better knowledge of the chemistry at the early stages of the Universe. The method uses previous information about the statistical properties of the sources, so that this knowledge is incorporated in a Bayesian scheme. Simulations show that our approach allows the detection of more sources than previous non-Bayesian techniques, with a small computation time.     

Subcentimeter depth resolution using a single-photon counting time-of-flight laser ranging system at 1550 nm wavelength

We demonstrate subcentimeter depth profiling at a stand off distance of 330 m using a time-of-flight approach based on time-correlated single-photon counting. For the first time to our knowledge, the photon-counting time-of-flight technique was demonstrated at a wavelength of 1550 nm using a superconducting nanowire single-photon detector. The performance achieved suggests that a system using superconducting detectors has the potential for low-light-level and eye-safe operation. The system's instrumental response was 70 ps full width at half-maximum, which meant that 1 cm surface-to-surface resolution could be achieved by locating the centroids of each return signal. A depth resolution of 4 mm was achieved by employing an optimized signal-processing algorithm based on a reversible jump Markov chain Monte Carlo method.     

SuFEx-enabled,chemoselective synthesis of triflates,triflamides and triflimidates

Sulfur(vi) Fluoride Exchange (SuFEx) chemistry has emerged as a next-generation click reaction, designed to assemble functional molecules quickly and modularly. Here, we report the ex situ generation of trifluoromethanesulfonyl fluoride (CF₃SO₂F) gas in a two chamber system, and its use as a new SuFEx handle to efficiently synthesize triflates and triflamides. This broadly tolerated protocol lends itself to peptide modification or to telescoping into coupling reactions. Moreover, redesigning the S^VI–F connector with a S O → S NR replacement furnished the analogous triflimidoyl fluorides as SuFEx electrophiles, which were engaged in the synthesis of rarely reported triflimidate esters. Notably, experiments showed H₂O to be the key towards achieving chemoselective trifluoromethanesulfonation of phenols vs. amine groups, a phenomenon best explained—using ab initio metadynamics simulations—by a hydrogen bonded termolecular transition state for the CF₃SO₂F triflylation of amines.

Triflyl fluoride gas (CF₃SO₂F) and its aza analogues are reported as new SuFEx activators. These S^VI–F reagents react efficiently with a variety of nucleophiles, yet the presence of water grants complete chemoselectivity to phenols.     

Machine Learning Algorithm to Predict Acidemia Using Electronic Fetal Monitoring Recording Parameters

Background: Electronic fetal monitoring (EFM) is the universal method for the surveillance of fetal well-being in intrapartum. Our objective was to predict acidemia from fetal heart signal features using machine learning algorithms. Methods: A case–control 1:2 study was carried out compromising 378 infants, born in the Miguel Servet University Hospital, Spain. Neonatal acidemia was defined as pH < 7.10. Using EFM recording logistic regression, random forest and neural networks models were built to predict acidemia. Validation of models was performed by means of discrimination, calibration, and clinical utility. Results: Best performance was attained using a random forest model built with 100 trees. The discrimination ability was good, with an area under the Receiver Operating Characteristic curve (AUC) of 0.865. The calibration showed a slight overestimation of acidemia occurrence for probabilities above 0.4. The clinical utility showed that for 33% cutoff point, missing 5% of acidotic cases, 46% of unnecessary cesarean sections could be prevented. Logistic regression and neural networks showed similar discrimination ability but with worse calibration and clinical utility. Conclusions: The combination of the variables extracted from EFM recording provided a predictive model of acidemia that showed good accuracy and provides a practical tool to prevent unnecessary cesarean sections.     

Self-similar vortex reconnection

As shown by Crow in 1970, the evolution of two almost parallel vortex filaments with opposite circulation exhibits a long-wave instability. Ultimately, the symmetric mode increases its amplitude reconnecting both filaments and ending into the formation of an almost periodic structure of vortex rings. This is a universal process, which appears in a wide range of scales: from the vortex trails behind an airplane to a microscopic scale of superfluids and Bose–Einstein condensates. In this paper, I will focus on the vortex reconnection for the latter case by employing Gross–Pitaevskii theory. Essentially, I focus on the well-known laws of interaction and motion of vortex filaments. By means of numerical simulations, as well as theoretically, I show that a self-similar finite-time dynamics manifests near the reconnection time. A self-similar profile is selected showing excellent agreement with numerical simulations.     

Simulation of Organic Liquid Product Deoxygenation through Multistage Countercurrent Absorber/Stripping Using CO2 as Solvent with Aspen-HYSYS: Process Modeling and Simulation

In this work, the deoxygenation of organic liquid products (OLP) obtained through the thermal catalytic cracking of palm oil at 450 °C, 1.0 atmosphere, with 10% (wt.) Na₂CO₃ as a catalyst, in multistage countercurrent absorber columns using supercritical carbon dioxide (SC-CO₂) as a solvent, with an Aspen-HYSYS process simulator, was systematically investigated. In a previous study, the thermodynamic data basis and EOS modeling necessary to simulate the deoxygenation of OLP was presented. This work addresses a new flowsheet, consisting of 03 absorber columns, 10 expansions valves, 10 flash drums, 08 heat exchanges, 01 pressure pump, and 02 make-ups of CO₂, aiming to improve the deacidification of OLP. The simulation was performed at 333 K, 140 bar, and (S/F) = 17; 350 K, 140 bar, and (S/F) = 38; 333 K, 140 bar, and (S/F) = 25. The simulation shows that 81.49% of OLP could be recovered and that the concentrations of hydrocarbons in the extracts of absorber-01 and absorber-02 were 96.95 and 92.78% (wt.) on a solvent-free basis, while the bottom stream of absorber-03 was enriched in oxygenated compounds with concentrations of up to 32.66% (wt.) on a solvent-free basis, showing that the organic liquid products (OLP) were deacidified and SC-CO₂ was able to deacidify the OLP and obtain fractions with lower olefin contents. The best deacidifying condition was obtained at 333 K, 140 bar, and (S/F) = 17.     

Rhodium-catalyzed intermolecular hydroacylation of 1-alkynes: Effect of phosphines and MK-10 on the reaction selectivity

The use of bulky ligands in the rhodium-catalyzed reaction of aldehydes 7 (R¹ = Ph) and 18 with 1-octyne increased the selectivity for ketones 13 and 20, to the detriment of ketones 12 and 19. Bulky phosphines reduced the hydroacylation reaction rate, leading to competition from the addition of the benzoic acid co-catalyst to the alkynes. This competing reaction can be suppressed by using the clay Montmorillonite K 10 (MK-10) as the co-catalyst instead of benzoic acid.     

Multi‐responses Methodology Applied in the Electroanalytical Determination of Hair Dye by Using Printed Carbon Electrode Modified with Graphene

This paper describes a rapid and sensitive method for determination of the hair dye Basic Blue 41 in wastewater samples using screen‐printed carbon electrodes modified with graphene (SPCE/Gr). The method is based on the reversible reduction of azo groups of the dye at potential of ?0.23 V/?0.26 V, where both the anodic and cathodic currents increased 1,300 % when compared to screen‐printed carbon (SPCE) and glassy carbon electrodes (GCE). The optimization of a square wave voltammetric method was performed by means of 2³ factorial design, Doehlert matrix and multi‐response assays, and the best parameters were: frequency (54.8 Hz), step potential (6 mV), pulse amplitude (43.7 mV) and pH 4.5. The analytical curve was constructed from 3.00×10^?8 to 2.01×10^?6 mol L^?1, with detection and quantification limits of 5.00×10^?9 and 1.70×10^?8 mol L^?1, respectively. The repeatability of the method evaluated for 10 consecutive measurements at concentrations of 1.70×10^?7 mol L^?1 and 1.70×10^?6 mol L^?1, showed relative standard deviation of 3.56 and 0.57 %, respectively. The sensor based in SPCE/Gr was successfully applied in wastewater samples collected from a drinking water treatment plant and validated by comparison with HPLC‐DAD method with good accuracy.