FTIR-ATR detection method for emerging C3-plants-derivated adulterants in honey: Beet, dates, and carob syrups.

The European Union Publications Office has recently presented a report on the European Union's coordinated action with the Joint Research Centre to determine certain fraudulent practices in the honey sector, in which it has been indicated that 74% of the samples analyzed, imported from China, and 93% of the samples analyzed, imported from Turkey, the two largest honey producers worldwide, presented at least one indicator of exogenous sugar or suspicion of being adulterated. This situation has revealed the critical state of the problem of honey adulteration worldwide and the need to develop analytical techniques for its detection. Even though the adulteration of honey is carried out in a general way with sweetened syrups derived from C4 plants, recent studies have indicated the emerging use of syrups derived from C3 plants for the adulteration of honey. This kind of adulteration makes it impossible to analyze its detection using official analysis techniques. In this work, we have developed a fast, simple, and economical method based on the Fourier transform infrared spectroscopy technique, with attenuated total reflectance, for the qualitative, quantitative, and simultaneous determination of beetroot, date, and carob syrups, derived from of C3 plants; whose available bibliography is very scarce and analytically not very conclusive for its use by the authorities. The proposed method has been based on the establishment of the spectral differences between honey and the mentioned syrups at eight different points in the spectral region between 1200 and 900 cm-1 of the mid-infrared, characteristic of the vibrational modes of carbohydrates in honey, which allows the pre-discrimination of the presence or absence of the syrups studied, and their subsequent quantification, with precision levels lower than 2.0% of the relative standard deviation and relative errors lower than 2.0% (m/m).

Rapid, reliable and easy-to-perform chemometric-less method for rice syrup adulterated honey detection using FTIR-ATR.

The adulteration of honey (Apis mellifera) is a global problem due to its economic, commercial and health implications. The world's leading beekeeping organisation, APIMONDIA, considers that the detection of adulteration in honey is a problem that has not yet been resolved. This evidence of the importance of the intensive development of analytical techniques that allow the unequivocal detection of adulterants in honey, especially those whose use as honey adulterants has recently emerged. This work aims to develop a fast, easy-to-perform, low-cost analytical method to qualitatively and quantitatively determine rice syrup using the Fourier transform infrared spectroscopy (FTIR) technique with attenuated total reflectance (ATR) mode without complex mathematical procedures and sophisticated sample preparation. This study involved the analysis of 256 intentionally rice-syrup-adulterated honey samples and 92 pure honey samples of bee multifloral honey from Spain. The method, based strictly on the determination of the absorbance directly from the samples, at 1013 cm-1 The methodology used no need for previous treatments or preparations and demonstrated the scope for the unequivocal detection of rice syrup in adulterated honey containing equal to or higher than 3% (m/m) or more of this adulterant. Using the Exponential Plus Linear model (r = 0.998) shows high accuracy and precision, in terms of relative error (0.32%, m/m) and coefficient of variation (1.4%). The results of this study have led to the establishment of a maximum absorbance threshold of 0.670 for honey without rice syrup.

Honey polyphenols: regulators of human microbiota and health.

A comprehensive review of research over the last decade was conducted to carry out this work. The main objective of this work is to present relevant evidence of the effect of honey intake on the human intestinal microbiota and its relationship with the improvement of various chronic diseases, such as cirrhosis, metabolic syndrome, diabetes, and obesity, among others. Therefore, this work focuses on the health-improving honey dietary supplementation implications associated with specific changes in the human microbiota and their biochemical mechanisms to enhance the proliferation of beneficial microorganisms and the inhibition of pathogenic microorganisms. Consumption of honey polyphenols significantly improves people's health conditions, especially in patients with chronic disease. Hence, honey intake unequivocally constitutes an alternative way to enhance health and could be used to prevent some relevant chronic diseases.

Heavy metal transport and evolution of atmospheric aerosols in the Antarctic region.

Suspended particulate matter (SPM) measurements and backward air mass trajectory analysis using the HYSPLIT model were performed to better understand the main sources and transport pathways of heavy metals in atmospheric aerosols reaching the Antarctic region. Field campaigns were carried out during the austral summer 2016-2017 at the "Gabriel de Castilla" Spanish Antarctic Research Station, located on Deception Island. Aerosols were deposited in an air filter through a low-volume sampler and chemically analysed using Inductively Coupled Plasma-Mass Spectrometry (ICP-MS). The study of air masses and high enrichment factor values of several elements (Hf, Zr, As, Cu, Sn, Zn, Pb) together with their correlations (Hf/Zr, V/As, Ti/Mn and Cu/Sn) suggests a potentially significant role of three main sources in this area: remote maritime traffic, local petrol combustion (generators and/or tourist cruises), and remote/local crust. Additionally, the investigation of atmospheric flow patterns through backward trajectory analysis revealed that Hf/Zr correlation was related to a remote crustal origin, V/As to anthropogenic local pollution, Ti/Mn to terrestrial inputs on the island and Cu/Sn to remote anthropogenic sources. Overall, the present study demonstrates the existence of anthropogenic pollution at this remote site from distant as well as local sources following the Antarctic circumpolar wind pattern.

Interferences in the transverse profile of a toluene beam induced by a resonant RF electric field.

In this work, the interaction of a supersonic beam of toluene diluted in He with a resonant oscillating RF field is investigated both experimental and theoretically. It is shown how the resonant field induces a peak structure in the transverse beam profile which can be explained by the onset of molecular interferences. Specifically, the interaction of a toluene beam of 0.12 eV of translational energy with a resonant RF field of 1.12 kV/m amplitude, and -610 kV/m(2) of gradient at the horizontal plane, during 160 micros produces a series of maxima in the transverse beam profile. The observed structure was satisfactorily reproduced by a quantum interference model based on the interaction of two coherent superpositions induced by the resonant RF field. It appears the present experimental technique could be useful to investigate the spectroscopy and dynamical behavior of coherent beams of polar molecules.

Quantification of particulate matter, tracking the origin and relationship between elements for the environmental monitoring of the Antarctic region.

The present work reports on the analysis of atmospheric aerosols in the Antarctic region, Deception Island, collected during austral summer 2016-2017 by field measurements carried from Gabriel de Castilla Spanish Research Station. A low-volume sampler was used to capture the aerosols depositing them onto the air filters. A chemical analysis of the samples using Inductively Coupled Plasma-Mass Spectrometry (ICP-MS) and Inductively Coupled Plasma-Atomic Emission Spectroscopy (ICP-AES) provided the total carbon (TC), organic carbon (OC), elemental Carbon (EC) and elements such as Al, Ca, Fe, K, Mg, Na, P, S, Cu, Pb, Sr, Ti, Zn and Cr. The average mass concentration of particulate matter (PM10) originated by natural and anthropogenic activities was calculated as 10 ±â€¯4 µg/m3, although values such as 28.2 µg/m3 were also obtained which is very high even when compared to other places in the coast of the Antarctic region. In addition, high enrichment factors have been found for elements such as Pb, Cr, Cu and Zn showing a remote anthropogenic contribution to particulate matter in this region. Correlations were found between Na, Mg, Ca, Al, Ti and S, where Na/Mg displayed the influence of marine environments, S correspond to volcanic activities, Ca to penguin colonies and influence of sea whereas Al/Ti indicated the crustal origin. Polar contour graphical maps were obtained from meteorological data using chemometrics methods, which allowed reproducing wind maps revealing the distribution of the aerosols and possible emission sources of different elements in the area. Given that this island has not been previously studied for atmospheric contamination, this work provides an interesting insight about the site-specific characteristics of particulate matter.

Qualitative and quantitative analysis of milk for the detection of adulteration by Laser Induced Breakdown Spectroscopy (LIBS).

The present work focuses on the development of a fast and cost effective method based on Laser Induced Breakdown Spectroscopy (LIBS) to the quality control, traceability and detection of adulteration in milk. Two adulteration cases have been studied; a qualitative analysis for the discrimination between different milk blends and quantification of melamine in adulterated toddler milk powder. Principal Component Analysis (PCA) and neural networks (NN) have been used to analyze LIBS spectra obtaining a correct classification rate of 98% with a 100% of robustness. For the quantification of melamine, two methodologies have been developed; univariate analysis using CN emission band and multivariate calibration NN model obtaining correlation coefficient (R2) values of 0.982 and 0.999 respectively. The results of the use of LIBS technique coupled with chemometric analysis are discussed in terms of its potential use in the food industry to perform the quality control of this dairy product.

Megapixel multi-elemental imaging by Laser-Induced Breakdown Spectroscopy, a technology with considerable potential for paleoclimate studies.

Paleoclimate studies play a crucial role in understanding past and future climates and their environmental impacts. Current methodologies for performing highly sensitive elemental analysis at micrometre spatial resolutions are restricted to the use of complex and/or not easily applied techniques, such as synchrotron radiation X-ray fluorescence micro-analysis (µ-SRXRF), nano secondary ion mass spectrometry (nano-SIMS) or laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS). Moreover, the analysis of large samples (>few cm²) with any of these methods remains very challenging due to their relatively low acquisition speed (~1-10 Hz), and because they must be operated in vacuum or controlled atmosphere. In this work, we proposed an imaging methodology based on laser-induced breakdown spectroscopy, to perform fast multi-elemental scanning of large geological samples with high performance in terms of sensitivity (ppm-level), lateral resolution (up to 10 µm) and operating speed (100 Hz). This method was successfully applied to obtain the first megapixel images of large geological samples and yielded new information, not accessible using other techniques. These results open a new perspective into the use of laser spectroscopy in a variety of geochemical applications.

Identification and Discrimination of Brands of Fuels by Gas Chromatography and Neural Networks Algorithm in Forensic Research.

The detection of adulteration of fuels and its use in criminal scenes like arson has a high interest in forensic investigations. In this work, a method based on gas chromatography (GC) and neural networks (NN) has been developed and applied to the identification and discrimination of brands of fuels such as gasoline and diesel without the necessity to determine the composition of the samples. The study included five main brands of fuels from Spain, collected from fifteen different local petrol stations. The methodology allowed the identification of the gasoline and diesel brands with a high accuracy close to 100%, without any false positives or false negatives. A success rate of three blind samples was obtained as 73.3%, 80%, and 100%, respectively. The results obtained demonstrate the potential of this methodology to help in resolving criminal situations.

Classification of red wine based on its protected designation of origin (PDO) using Laser-induced Breakdown Spectroscopy (LIBS).

This work reports on a simple and fast classification procedure for the quality control of red wines with protected designation of origin (PDO) by means of Laser Induced Breakdown Spectroscopy (LIBS) technique combined with Neural Networks (NN) in order to increase the quality assurance and authenticity issues. A total of thirty-eight red wine samples from different PDO were analyzed to detect fake wines and to avoid unfair competition in the market. LIBS is well known for not requiring sample preparation, however, in order to increase its analytical performance a new sample preparation treatment by previous liquid-to-solid transformation of the wine using a dry collagen gel has been developed. The use of collagen pellets allowed achieving successful classification results, avoiding the limitations and difficulties of working with aqueous samples. The performance of the NN model was assessed by three validation procedures taking into account their sensitivity (internal validation), generalization ability and robustness (independent external validation). The results of the use of a spectroscopic technique coupled with a chemometric analysis (LIBS-NN) are discussed in terms of its potential use in the food industry, providing a methodology able to perform the quality control of alcoholic beverages.

Laser induced breakdown spectroscopy for the discrimination of Candida strains.

The present study reports the evaluation of Laser Induced Breakdown Spectroscopy (LIBS) and Neural Networks (NN) for the discrimination of different strains of various species of Candida. This genus of yeast was selected due to its medical relevance as it is commonly found in cases of fungal infection in humans. Twenty one strains belonging to seven species of Candida were included in the study. Scanning Electron Microscopy with Energy-Dispersive X-ray Spectroscopy (SEM-EDS) was employed as a complementary technique to provide information about elemental composition of Candida cells. The use of LIBS spectra in combination with optimized NN models provided reliable discrimination among the distinct Candida strains with a high spectral correlation index for the samples analyzed, without any false positive or false negative. Therefore, this study indicates that LIBS-NN based methodology has the potential to be used as fast fungal identification or even diagnostic method.

The relationship between the sensation of incomplete voiding and a high postvoid residual volume. / La relación entre la sensación de vaciado incompleto y un residuo posmiccional elevado.

BACKGROUND: Studies have shown that voiding symptoms do not correlate with a high postvoid residual volume. It is important to have clinical tools that help make early and effective decisions during the initial consultation. OBJECTIVE: To assess the validity and degree of concordance between the sensation of incomplete voiding and high postvoid residual volume. MATERIAL AND METHODS: Cross-sectional study of patients who underwent uroflowmetry (UFM) and postvoid residual volume (PVR) measurement due to lower urinary tract symptoms, with simultaneous scoring of International Prostate Symptom Score (IPSS), the International Consultation on Incontinence Questionnaire - Female Lower Urinary Tract Symptoms (ICIQ-FLUTS) or Male Lower Urinary Tract Symptoms (ICIQ-MLUTS) during 2014-2015. We analysed the relationship between these data and the postvoid residual volume. RESULTS: The study included 303 patients, 75 (24.8%) of whom were women and 228 (75.2%) of whom were men. The mean age was 60.9 years (SD, 15.8), and the mean Qmax was 14.47mL/s (SD, 9.6). Sixty (19.8%) patients had a high PVR. We detected 240 (79.2%) patients with sensations of incomplete voiding (SIV), but its presence was not associated with a high PVR in the population. For the SIV, the sensitivity, specificity, positive and negative predictive values and positive and negative likelihood ratios were 81.6%, 21.3%, 20.4%, 82.5%, 1.03 and 0.85, respectively. The area under the curve for the frequency of SIV was 0.52 (95%CI, 0.44-0.60, P=.5). The degree of concordance between SIV and high PVR was 0.014 (P=.6). In the ICIQ-MLUTS, PVR correlated with intermittence (Rho=0.132, P=.043) but not with SIV (Rho=0.09, P=.15). In the ICIQ-FLUTS, the frequency of urinary incontinence was positively correlated with PVR (Rho=0.216, P=.026). CONCLUSIONS: The sensation of incomplete voiding is not associated with a high postvoid residual volume. Other variables such as symptom severity, urinary effort and total score for voiding symptoms can be associated with a high residual urine volume.

A methodological framework for estimating ambient PM2.5 particulate matter concentrations in the UK.

Scientific evidence sustains PM2.5 particles' inhalation may generate harmful impacts on human beings' health; therefore, their monitoring in ambient air is of paramount relevance in terms of public health. Due to the limited number of fixed stations within the air quality monitoring networks, development of methodological frameworks to model ambient air PM2.5 particles is primordial to providing additional information on PM2.5 exposure and its trends. In this sense, this work aims to offer a global easily-applicable tool to estimate ambient air PM2.5 as a function of meteorological conditions using a multivariate analysis. Daily PM2.5 data measured by 84 fixed monitoring stations and meteorological data from ERA5 (ECMWF Reanalysis v5) reanalysis daily based data between 2000 and 2021 across the United Kingdom were attended to develop the suggested approach. Data from January 2017 to December 2020 were employed to build a mathematical expression that related the dependent variable (PM2.5) to predictor ones (sea-level pressure, planetary boundary layer height, temperature, precipitation, wind direction and speed), while 2021 data tested the model. Evaluation indicators evidenced a good performance of model (maximum values of RMSE, MAE and MAPE: 1.80 µg/m3, 3.24 µg/m3, and 20.63%, respectively), compiling the current legislation's requirements for modelling ambient air PM2.5 concentrations. A retrospective analysis of meteorological features allowed estimating ambient air PM2.5 concentrations from 2000 to 2021. The highest PM2.5 concentrations relapsed in the Mid- and Southlands, while Northlands sustained the lowest concentrations.

Rapid identification and discrimination of bacterial strains by laser induced breakdown spectroscopy and neural networks.

Identification and discrimination of bacterial strains of same species exhibiting resistance to antibiotics using laser induced breakdown spectroscopy (LIBS) and neural networks (NN) algorithm is reported. The method has been applied to identify 40 bacterial strains causing hospital acquired infections (HAI), i.e. Pseudomonas aeruginosa, Escherichia coli, Klebsiella pneumoniae, Salmonella typhimurium, Salmonella pullurum and Salmonella salamae. The strains analyzed included both isolated from clinical samples and constructed in laboratory that differ in mutations as a result of their resistance to one or more antibiotics. Small changes in the atomic composition of the bacterial strains, as a result of their mutations and genetic variations, were detected by the LIBS-NN methodology and led to their identification and classification. This is of utmost importance because solely identification of bacterial species is not sufficient for disease diagnosis and identification of the actual strain is also required. The proposed method was successfully able to discriminate strains of the same bacterial species. The optimized NN models provided reliable bacterial strain identification with an index of spectral correlation higher than 95% for the samples analyzed, showing the potential and effectiveness of the method to address the safety and social-cost HAI-related issue.

Identification and discrimination of bacterial strains by laser induced breakdown spectroscopy and neural networks.

A method based on laser induced breakdown spectroscopy (LIBS) and neural networks (NNs) has been developed and applied to the identification and discrimination of specific bacteria strains (Pseudomonas aeroginosa, Escherichia coli and Salmonella typhimurium). Instant identification of the samples is achieved using a spectral library, which was obtained by analysis using a single laser pulse of representative samples and treatment by neural networks. The samples used in this study were divided into three groups, which were prepared on three different days. The results obtained allow the identification of the bacteria tested with a certainty of over 95%, and show that only a difference between the bacteria can cause identification. Single-shot measurements were sufficient for clear identification of the bacterial strains studied. The method can be developed for automatic real time, fast, reliable and robust measurements and can be packaged in portable systems for non-specialist users.

Methods for measuring abdominal obesity in the prediction of severe acute pancreatitis, and their correlation with abdominal fat areas assessed by computed tomography.

BACKGROUND: Obesity increases the risk for severe acute pancreatitis, although abdominal obesity may be a better prognostic marker. AIM: To determine if a single anthropometric parameter best predicts severe acute pancreatitis and correlates with intra-abdominal fat. METHODS: Ninety-nine patients with acute pancreatitis were studied prospectively. Anthropometry included body mass index (BMI) and girths (umbilical/minimum waist, iliac/trochanter hip, thigh). Several waist-to-hip/waist-to-thigh ratios (WHR/WTR) were constructed. A CT-scan with calculation of cross-sectional abdominal fat areas was obtained in 37 cases. RESULTS: Severe acute pancreatitis occurred in 25 patients. Waist circumference (WC), WHR and WTR - all using the umbilical reference - most accurately predicted severe acute pancreatitis. Only umbilical WC was retained in multivariate analysis: the risk for severe acute pancreatitis increased 16% with every 1 cm (OR 1.16, 95%CI: 1.1-1.3). Abdominal obesity caused a 6-fold increase in risk. Umbilical WC correlated best with subcutaneous fat area (r = 0.791, P < 0.001), whereas WHR with intra-abdominal (r = 0.594, P < 0.001). CONCLUSIONS: Abdominal obesity according to umbilical WC is a better predictor for development of severe acute pancreatitis than BMI, minimum WC, WHR and WTR. The protocol for anthropometry must be standardized as it may affect results. Both subcutaneous and intra-abdominal fat appears to affect the likelihood of a severe outcome.

Interaction of polar molecules with resonant radio frequency electric fields: imaging of the NO molecular beam splitting.

The interaction between a NO supersonic beam and a resonant radio frequency (RF) field is investigated using laser ionization coupled to imaging techniques. It is shown how the resonant interaction leads to a beam splitting of +/-0.2 degrees toward both positive and negative direction perpendicular to the beam propagation axis. This phenomenon is rationalized using a model based on molecular interferences produced by the action of the resonant RF electric field.