Identification Of Analytes Research Articles

Comparison between Phenotypic and Genotypic Detection of Metallo Beta Lactamase Enzyme among Gram Negative Bacteria Isolated from Burn Patient

Background: -lactamases (MBLs) are emerging worldwide as powerful resistance determinants in Gram negative bacteria Rapid dissemination and spread between different bacterial species by large gene transfer favor by globalization and travel represent a high risk of worldwide pandemic among Enterobacteriaceae Objective:This study design to screen for phenotypic detection of MBL and genes coding for metallo - lactamase(MBL) such as, blaVIM, blaIMP and bla NDM among infected burn wound patients in Sulaimani city /Iraq. Materials and Methods: Out of 230 burn wound samples, 201 wound swabs and 29 tissue biopsy were collected from hospitalized burn patients with second and third degrees burnfrom Burn and Plastic Surgery Hospital in Sulaimani city from the period of April to October 2011. According to direct gram stain , bacterial cultural , biochemical tests, analytic profile identification(API) system and vitek 2 Compact system , antimicrobial susceptibility Testing by using Kirby-Bauer disk diffusion method and vitek compact system, -lactamase by Double disk synergy test and Combined EDTA disk test and Modified Hodge test and -lactamase enzyme by using polymerase chain reaction. Results: Out of 230 burn wound samples177 samples gram negative bacteria were isolated; inflammatory cells showed significantly associated with positive bacterial culture. The most frequent bacteria isolated were Pseudomonas species 48(27.12%), in which Pseudomonas aeruginosa account for a higher percentage 46(25.98%) and one species (0.56%) of each P. stutzeri and P.florescence wasisolated followed by Acinetobacterspecies 44 (24.86%) in which Acinetobacterbaumanniiwas the commonest and accounts for a higher percentage 41 (23.16%) and one species(0.56%) of each of A. ursingi, A. hemolyticasandA.complexwere identified. On the other hand in the family of Enterobacteriaceae,the most common bacteria were Klebsiellapneumoniae44(24.86%), Enterobacter cloacae 18 (10.17%) and Escherichia species 11(6.21%). The susceptibility of bacterial isolates against 18 antibiotics from different classes of antibiotics was tested and it was found that most of the isolated species of non fermenter bacteria such as Acinetobacterand Pseudomonas species show multidrug resistant pattern and high resistance against most of the antibiotics commonly used. The most resistant antibiotics against non fermenter bacteria were Ticarcillin (81.82%) against Pseudomonas species and Ticarcillin, Tazobactam- Pipracillin and Cefoxitin (93.18%) against Acinetobacterspecies .The most resistant antibiotic against K. pneumonia andE.cloacaewere Cefoxitin(84.9%)and Amoxicillin Clavulanic acid (84.9%).The most resistant antibiotics against Escherichia specieswere Cefotaxime, Trimethoprim and Cefipime (90.91%) but the most effective antibiotic with a highsensitivity rate was Imipenem (90.91).Phenotypic tests were carried out for the detection of MBL enzyme for all studied isolates and it was found that Combined disk test was the most sensitive test giving the highest percentage (31.07%) followed by Double disk synergy test(28.8%), Modified Hodge test (20.9%) .Polymerase chain reaction assay was used for genotypic detection of MBL genes (blaIMP,blaVIM, ,blaNDM ) in all isolates and the results revealed that the gene blaIMPwas locatedin 33(18.64%),blaVIM,in19 (10.73%), 2(1.12%)forblaNDM Also these genes were detected in 25 stock cultures of Gram negative bacteria preserved in 25 °C since 2008 to 2010. blaIMP gene was detected in11(44%) , blaVIM in 12(48%) and 2(8%) for blaNDM, all these genes were detected in K. pneumonae,P. aeruginosa and A. baumanniiwith length amplified genes (230) bp for IMP and (390)bp for VIM and( 621)bp for NDM. Conclusions:These results indicate that most of the Meropenem resistant strains from infected burn wound strains in this study were producing MBL enzymes The presence of MBL genes among Meropenem sensitive strains indicates that there might be a hidden MBL gene among isolated strains which cannot be diagnosed by phenotypic tests leading to the dissemination of these genes in the hospital silently among patients even within normal health workers who act as carriers for MBL genes in future

Class comparison enabled mass spectrum purification for comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry

Tile-based Fisher ratio (F-ratio) analysis is emerging as a versatile data analysis tool for supervised discovery-based experimentation using comprehensive two-dimensional (2D) gas chromatography coupled with time-of-flight mass spectrometry (GC × GC-TOFMS). None the less, analyte identification can often be marred by poor 2D resolution and low analyte abundance relative to overlapping compounds. Linear algebra-based chemometric methods, in particular multivariate curve resolution alternating least squares (MCR-ALS), parallel factor analysis (PARAFAC) and PARAFAC2, are often applied in an effort to address this situation. However, these chemometric methods can fail to produce an accurate spectrum when the analyte is at low 2D resolution and/or in low relative abundance. To address this challenge, we introduce class comparison enabled mass spectrum purification (CCE-MSP), a method that utilizes the underlying requirement for signal consistency of the background interference compounds between the two classes in the F-ratio analysis to purify the mass spectrum of the analyte hits. CCE-MSP is validated using a dataset obtained for a neat JP-8 jet fuel spiked with 14 sulfur containing compounds at two levels (15 ppm and 30 ppm), using the p-value and lack-of-fit (LOF) for each analyte hit as consistency metrics. A purified mass spectrum was produced for each spiked analyte hit and their mass spectrum match value (MV) was compared to the MV obtained by MCR-ALS, PARAFAC, and PARAFAC2. The resulting MV for CCE-MSP were found to be as good or better than these chemometric methods, eg., for 2-butyl-5-ethylthiophene with an analyte-to-interference relative signal abundance of 1:87 and a 2D resolution of 0.2, CCE-MSP produced a MV of 831, compared to 476 for MCR-ALS, 403 for PARAFAC, and 336 for PARAFAC2. CCE-MSP is also extended to obtain the purified spectrum for more than one analyte, eg., two analyte hits in overlapping hit locations. The spectra produced by CCE-MSP can also be utilized as estimates to facilitate quantitative signal decomposition using MCR-ALS.

MONITORING OF AIR AND SURFACE WATER POLLUTION IN THE RYAZAN REGION

Aim: To perform expert assessment of monitoring data on air pollution and surface water in the Ryazan region, Central Russia. Methods: A descriptive study. The information of state standards and regulations in the field of sanitation and hygiene, local acts in the field of environmental monitoring, a number of federal and regional statistical books were studied, analyzed and systematized. Screening evaluation of the analytical information, identification and generalization of problems in the existing system of chemical monitoring and identification of hazards and risks were done. We used a method for analyzing and synthesizing statistical information and a method of converting absolute values to relative values. The system analysis allowed us to draw conclusions and recommendations and to suggest the directions for further research. Results: The analysis of atmospheric air and surface water pollution information in the Ryazan region is presented. The urgent need to change the existing system for monitoring atmospheric air and surface water is shown. The ways of the environment chemical monitoring effectiveness increasing and increasing the level of objectivity of environmental quality assessment procedures in the Ryazan region are outlined. The necessity of working and organizing a system of continuous operational monitoring of environmental components, monitoring of toxicants and implementation of independent expert monitoring of environment components with the further going aim to develop "Medical and ecological Atlas of Ryazan region". Conclusions: The situation with chemical pollution of the atmosphere and surface water objects in the Ryazan region has been stagnating since the 1990s. Periodic ultra-high pollution parameters were detected, in some cases exceeding the maximum permissible standards by tens and hundreds of times. The solution of the effectiveness and environmental quality assessment reliability problem lies in the improvement of the state monitoring system and the support of independent expert monitoring.

Moving toward a Handheld "Plasma" Spectrometer for Elemental Analysis, Putting the Power of the Atom (Ion) in the Palm of Your Hand.

Many of the current innovations in instrument design have been focused on making them smaller, more rugged, and eventually field transportable. The ultimate application is obvious, carrying the instrument to the field for real time sample analysis without the need for a support laboratory. Real time data are priceless when screening either biological or environmental samples, as mitigation strategies can be initiated immediately upon the discovery that contaminant metals are present in a location they were not intended to be. Additionally, smaller “handheld” instruments generally require less sample for analysis, possibly increasing sensitivity, another advantage to instrument miniaturization. While many other instruments can be made smaller just by using available micro-technologies (e.g., eNose), shrinking an ICP-MS or AES to something someone might carry in a backpack or pocket is now closer to reality than in the past, and can be traced to its origins based on a component-by-component evaluation. While the optical and mass spectrometers continue to shrink in size, the ion/excitation source remains a challenge as a tradeoff exists between excitation capabilities and the power requirements for the plasma’s generation. Other supporting elements have only recently become small enough for transport. A systematic review of both where the plasma spectrometer started and the evolution of technologies currently available may provide the roadmap necessary to miniaturize the spectrometer. We identify criteria on a component-by-component basis that need to be addressed in designing a miniaturized device and recognize components (e.g., source) that probably require further optimization. For example, the excitation/ionization source must be energetic enough to take a metal from a solid state to its ionic state. Previously, a plasma required a radio frequency generator or high-power DC source, but excitation can now be accomplished with non-thermal (cold) plasma sources. Sample introduction, for solids, liquids, and gasses, presents challenges for all sources in a field instrument. Next, the interface between source and a mass detector usually requires pressure reduction techniques to get an ion from plasma to the spectrometer. Currently, plasma mass spectrometers are field ready but not necessarily handheld. Optical emission spectrometers are already capable of getting photons to the detector but could eventually be connected to your phone. Inert plasma gas generation is close to field ready if nitrogen generators can be miniaturized. Many of these components are already commercially available or at least have been reported in the literature. Comparisons to other “handheld” elemental analysis devices that employ XRF, LIBS, and electrochemical methods (and their limitations) demonstrate that a “cold” plasma-based spectrometer can be more than competitive. Migrating the cold plasma from an emission only source to a mass spectrometer source, would allow both analyte identification and potentially source apportionment through isotopic fingerprinting, and may be the last major hurdle to overcome. Finally, we offer a possible design to aid in making the cold plasma source more applicable to a field deployment.

Screening of seized drugs utilizing portable Raman spectroscopy and direct analysis in real time-mass spectrometry (DART-MS)

The continuous change of the drug landscape in the United States demands adaptation and incorporation of emerging analytical methods that preferably allow onsite screening but are also capable of supporting the analysis of seized drugs received at forensic laboratories across the country. Current methods employing color testing require the interaction of chemical reagents with powdered and liquid materials and can often yield inconclusive results, especially when the material is impure.Implementation of portable Raman spectroscopy can remove the need for direct interaction with solid and liquid specimens. In this study a portable, 785 nm, Raman spectroscopy system was employed for screening of seized drug samples, including mixtures. First, a panel of analytes comprised of 15 common drugs of abuse, 15 diluents, and 64 different mixtures comprising various ratios of analytes were used to measure bias, precision, and repeatability in accordance with United Nations Office on Drugs and Crime (UNODC) guidelines for handheld Raman field identification devices for seized material. Accuracy and precision through glass packaging was 91% and 90%; and through plastic was 89% and 88%, respectively for the diluents examined. A subset of the pure and mixture samples was then analyzed using direct analysis in real time mass spectrometry (DART-MS). Identification of analytes was performed manually by observing the [M+H]+ protonated molecule and conducting a library search of an in-house database. Using DART-MS, the drug analyte present in the sample was correctly identified 92% of the time using the library search feature. The presence of dimers and –OH losses were also observed for many of the analyte drugs of abuse. The combination of portable Raman spectroscopy and DART-MS data resulted in an overall accuracy of 96% for the detection of both drugs and diluents. The combined accuracy when analyzing authentic case samples was 83%, providing a rapid and accurate method for seized drug screening within drug chemistry laboratories.

Single-Cell Mass Spectrometry Imaging of Multiple Drugs and Nanomaterials at Organelle Level.

Mass spectrometry imaging (MSI) techniques make possible the spatial chemical identification of analytes, especially for biological samples. As a universal energy source, laser is one of the most commonly used sampling methods in MSI techniques. However, due to the limitation of laser spot size, subcellular spatial resolution imaging, which is significant for life science researches, always remains a challenge for laser-based MSI. In this research, we designed a laser ablation (LA) system with a microlensed fiber and a "three-way" structure ablation chamber, and achieved nanoscale inductively coupled plasma (ICP) MSI with an adjustable spatial resolution down to 400 nm, which surpasses most existing technologies. With this device, the distribution of various photodynamic therapy drugs in the intestine of mouse can be clearly observed. The comparison imaging results showed that the drug distribution in tissue slice could be identified at the subcellular level with the high-resolution mode. More valuably, gold nanorods (GNRs) and carboplatin in a single cell are able to be visualized at organelle level due to the nanoscale resolution, which is able to reveal the mechanism of cell apoptosis. This reliable and economical MSI technique is expected to be used in understanding the precise chemical composition and transportation in small tissues, microorganisms, and single cells.

A Simple Analytical Method for Estimation of the Five-Parameter Model: Second-Order with Zero Plus Time Delay

Process models play an important role in the process industry. They are used for simulation purposes, quality control, fault detection, and control design. Many researchers have been engaged in model identification. However, it is difficult to find an analytical identification method that provides a good model and requires a relatively simple experiment. This is the advantage of the method of moments. In this paper, an analytical method based on the measurement of the process moments (characteristic areas) is proposed, to identify the five-parameter model (second-order process with zero plus time delay) from either the closed-loop or open-loop time responses of the process (in the time-domain), or the general-order transfer function with time delay (in the frequency-domain). The only parameter required by the user is the type of process (minimum phase or non-minimum phase process), which in practice can be easily determined from the time response of the process. The method can also be used to reduce the higher-order process model. The proposed identification method was tested on several illustrative examples, and compared to other identification methods. The comparison with existing methods showed the superiority of the proposed method. Moreover, the tests confirmed that the algorithm of the proposed method works properly for a wide family of process models, even in the presence of moderate process noise.

Double poroelasticity derived from the microstructure

We derive the balance equations for a double poroelastic material which comprises a matrix with embedded subphases. We assume that the distance between the subphases (the local scale) is much smaller than the size of the domain (the global scale). We assume that at the local scale both the matrix and subphases can be described by Biot’s anisotropic, heterogeneous, compressible poroelasticity (i.e. the porescale is already smoothed out). We then decompose the spatial variations by means of the two-scale homogenization method to upscale the interaction between the poroelastic phases at the local scale. This way, we derive the novel global scale model which is formally of poroelastic-type. The global scale coefficients account for the complexity of the given microstructure and heterogeneities. These effective poroelastic moduli are to be computed by solving appropriate differential periodic cell problems. The model coefficients possess properties that, once proved, allow us to determine that the model is both formally and substantially of poroelastic-type. The properties we prove are a) the existence of a tensor which plays the role of the classical Biot’s tensor of coefficients via a suitable analytical identity and b) the global scale scalar coefficient bar{mathcal {M}} is positive which then qualifies as the global Biot’s modulus for the double poroelastic material.

Seizures of New Psychoactive Substances on the Italian territory during the COVID-19 pandemic

In recent years, the availability and the consequent consumption of New Psychoactive Substances (NPS) have proliferated at an unprecedented rate, posing a significant risk to the public health and challenging the law enforcement efforts to tackle the black market. In particular, large availability on Internet and unmonitored shipping have facilitated the diffusion of NPS on national territories. In this scenario, the forensic activity based on the process of drug detection, including investigation, seizure, recognition and analytical identification is crucial to get insights into the drug black market transformation. In this study, we describe the results obtained from the analysis of hundreds of packages seized during the months of year 2020, and suspected to contain NPS because not reacting with standard field test kits. We focused on the analysis by GC-MS and HPLC-HRMS, and NPS in particular, trying to underline the most common molecules present on the Italian territory during the COVID-19 pandemic. NPS were identified in 92.6% of the samples. The most prevalent compounds were synthetic cathinones, and 3-MMC in particular, which alone accounted for 18.6% of the total cases. Other prevalent molecules were 5F-MDMB-PICA, 2-FDCK, 1cp-LSD and 1P-LSD. Fentanyl was never detected. The information obtained from drug seizures is crucial to publish national alerts, which are in turn important to assist the legislative effort to ban new compounds and the update of toxicological and analytical methods.

Abstract 473: Glycomic characterization of carbohydrate antigen-defined pancreatic cancer tissues using lectins and imaging mass spectrometry

Abstract N-glycosylation alterations in tumors are now recognized as cancer hallmarks for its role in oncogenesis, cancer signaling and metastasis. For pancreatic adenocarcinoma (PDAC), the sole FDA-approved biomarker is the carbohydrate antigen 19-9 (CA19-9). Because of CA19-9's association with pancreatitis and other gastrointestinal cancers, it is used for surveillance of disease progression rather than for diagnosis. A recently identified carbohydrate antigen, sialylated tumor-related antigen (sTRA) recognized by the TRA-1-60 mAb, is expressed in a non-overlapping subset of pancreatic cancer and is under consideration for use alongside CA19-9. To better understand these carbohydrate antigens in relation to PDAC pathogenesis, complementary N-glycan analysis approaches were applied to a cohort of 53 patient-matched tumor and normal tissue samples represented by tissue microarrays (TMA) and whole-tissue FFPE samples. The distribution of N-glycans in these tissues were defined using a matrix-assisted laser desorption ionization imaging mass spectrometry (MALDI-IMS) workflow. Over 100 individual N-glycan species were mapped to their histopathology locations. The same cohort was characterized by multi-round immunofluorescence for CA19-9 and sTRA expression as well as two lectins, PHA-E and GSL-II,. N-glycan IMS data from the TMAs were evaluated by LASSO-regularized logistic regression for the identification of N-glycan analytes with predictive value in differentiating between tumor and normal tissue. LASSO selected N-glycan masses were incorporated alongside biomarker expression data to construct a model for PDAC tissue classification. N-glycans associated with tumor tissue tended to be bi-, tri- and tetra-antennary complex structures with multople fucose, terminal sialic acids and bisecting GlcNAc. Quantitative analysis of the IMS data by LASSO regression identified 9 differentiating N-glycan masses, 7 from tumor cores and 2 from normal cores. When both IMS glycan masses and biomarker expression data for CA19-9 and sTRA were integrated into a single linear regression model, receiver operator curve (ROC) accuracy and AUC improvements, +0.172 and +0.221 respectively, were observed in comparison to models utilizing either dataset individually. Critically, this model was able to rescue cases where biomarker data was missing or insufficient so that they could be correctly classified as tumor or normal tissue. Analysis of this PDAC tissue cohort using MALDI-IMS illustrated the utility of investigating specific N-glycans and N-glycan structural classes correlated with carbohydrate PDAC biomarkers. Integration of N-glycan IMS and biomarker lectin immunostaining bolsters pancreatic cancer identification and posits expanded utility for each approach for PDAC surveillance and early identification. Citation Format: Colin McDowell, Zachary Klamer, Johnathan Hall, Luke Wisniewski, Peggi Angel, Anand Mehta, Brian Haab, Richard R. Drake. Glycomic characterization of carbohydrate antigen-defined pancreatic cancer tissues using lectins and imaging mass spectrometry [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 473.

Exploring miRNA Signature and Other Potential Biomarkers for Oligometastatic Prostate Cancer Characterization: The Biological Challenge behind Clinical Practice. A Narrative Review.

Simple SummaryThe oligometastatic prostate cancer state is defined as the presence of a number of lesions ≤ 5 and has been significantly correlated with better survival if compared to a number of metastases > 5. In particular, patients in an oligometastatic setting could benefit from a metastates directed therapy, which could control the disease delaying the start of systemic therapies. For this reason, the selection of true-oligometastatic patients who could benefit from such approach is particularly important in this setting. The aim of the present narrative review is to report the current state of the art on the liquid biopsy-derived analytes and their reliability as biomarkers in the clinics for the identification of true-oligometastatic patients. This kind of molecular profiling could refine current developments in the era of precision oncology allowing patients’ stratification and leading to more refined therapeutic strategies.In recent years, a growing interest has been directed towards oligometastatic prostate cancer (OMPC), as patients with three to five metastatic lesions have shown a significantly better survival as compared with those harboring a higher number of lesions. The efficacy of local ablative treatments directed on metastatic lesions (metastases-directed treatments) was extensively investigated, with the aim of preventing further disease progression and delaying the start of systemic androgen deprivation therapies. Definitive diagnosis of prostate cancer is traditionally based on histopathological analysis. Nevertheless, a bioptic sample—static in nature—inevitably fails to reflect the dynamics of the tumor and its biological response due to the dynamic selective pressure of cancer therapies, which can profoundly influence spatio-temporal heterogeneity. Furthermore, even with new imaging technologies allowing an increasingly early detection, the diagnosis of oligometastasis is currently based exclusively on radiological investigations. Given these premises, the development of minimally-invasive liquid biopsies was recently promoted and implemented as predictive biomarkers both for clinical decision-making at pre-treatment (baseline assessment) and for monitoring treatment response during the clinical course of the disease. Through liquid biopsy, different biomarkers, commonly extracted from blood, urine or saliva, can be characterized and implemented in clinical routine to select targeted therapies and assess treatment response. Moreover, this approach has the potential to act as a tissue substitute and to accelerate the identification of novel and consistent predictive analytes cost-efficiently. However, the utility of tumor profiling is currently limited in OMPC due to the lack of clinically validated predictive biomarkers. In this scenario, different ongoing trials, such as the RADIOSA trial, might provide additional insights into the biology of the oligometastatic state and on the identification of novel biomarkers for the outlining of true oligometastatic patients, paving the way towards a wider ideal approach of personalized medicine. The aim of the present narrative review is to report the current state of the art on the solidity of liquid biopsy-related analytes such as CTCs, cfDNA, miRNA and epi-miRNA, and to provide a benchmark for their further clinical implementation. Arguably, this kind of molecular profiling could refine current developments in the era of precision oncology and lead to more refined therapeutic strategies in this subset of oligometastatic patients.

A review of extraction, analytical, and advanced methods for the determination of neonicotinoid insecticides in environmental water matrices

AbstractNeonicotinoid insecticides are widely used to kill and prevent unwanted insects from attacking growing crops. Extensive use of insecticides in various compartments of the environment has led to adverse effect on the health of living organisms. Several analytical methodologies have been reported for extraction and quantification of neonicotinoid insecticides in various matrices. The analytical detection techniques range from traditional to modern or state of the art quantification methods. The traditional analytical techniques include gas chromatography and high-performance liquid chromatography. These methods require extensive sample pretreatment before identification, separation, and quantification of target analytes. Advanced detection techniques refer to the sensor technologies based on optical, biorecognition, molecular imprinted polymers chemical, and piezoelectric. In this review, a summary and explanation of the various traditional analytical and advanced methodologies for extraction, separation, detection, and quantification of neonicotinoid insecticides residue in water samples have been discussed.

All-Dielectric Metasurface for Sensing Microcystin-LR

Sensing Microcystin-LR (MC-LR) is an important issue for environmental monitoring, as the MC-LR is a common toxic pollutant found in freshwater bodies. The demand for sensitive detection method of MC-LR at low concentrations can be addressed by metasurface-based sensors, which are feasible and highly efficient. Here, we demonstrate an all-dielectric metasurface for sensing MC-LR. Its working principle is based on quasi-bound states in the continuum mode (QBIC), and it manifests a high-quality factor and high sensitivity. The dielectric metasurface can detect a small change in the refractive index of the surrounding environment with a quality factor of ~170 and a sensitivity of ~788 nm/RIU. MC-LR can be specifically identified in mixed water with a concentration limit of as low as 0.002 μg/L by a specific recognition technique for combined antigen and antibody. Furthermore, the demonstrated detection of MC-LR can be extended to the identification and monitoring of other analytes, such as viruses, and the designed dielectric metasurface can serve as a monitor platform with high sensitivity and high specific recognition capability.

The Analytic Identification of Variance Component Models Common to Behavior Genetics.

Many behavior genetics models follow the same general structure. We describe this general structure and analytically derive simple criteria for its identification. In particular, we find that variance components can be uniquely estimated whenever the relatedness matrices that define the components are linearly independent (i.e., not confounded). Thus, we emphasize determining which variance components can be identified given a set of genetic and environmental relationships, rather than the estimation procedures. We validate the identification criteria with several well-known models, and further apply them to several less common models. The first model distinguishes child-rearing environment from extended family environment. The second model adds a gene-by-common-environment interaction term in sets of twins reared apart and together. The third model separates measured-genomic relatedness from the scanner site variation in a hypothetical functional magnetic resonance imaging study. The computationally easy analytic identification criteria allow researchers to quickly address model identification issues and define novel variance components, facilitating the development of new research questions.

Comparison of analyte identification criteria and other aspects in triple quadrupole tandem mass spectrometry: Case study using UHPLC-MS/MS for regulatory analysis of veterinary drug residues in liquid and powdered eggs.

Ultrahigh-performance liquid chromatography (UHPLC) coupled with triple quadrupole tandem mass spectrometry (MS/MS) is one of the most powerful tools for the multiclass, multiresidue analysis of veterinary drugs, pesticides, mycotoxins, and other chemical contaminants in foods and other sample types. Until approximately 2010, commercial MS/MS instruments using multiple reaction monitoring (MRM) were generally limited to minimum dwell (and inter-dwell) times of 10ms per ion transition. To achieve the needed accuracy and detection limits for hundreds of targeted analytes, older UHPLC-MS/MS methods typically acquired only two ion transitions per analyte (yielding only one ion ratio for qualitative identification purposes), which is still the norm despite technological advancements. Newer instruments permit as little as 1ms (inter-)dwell times to afford monitoring of more MRMs/analyte with minimal sacrifices in accuracy and sensitivity. In this study, quantification and identification were assessed in the validation of 169 veterinary drugs in liquid and powdered eggs. Quantitatively, an "extract-and-inject" sample preparation method yielded acceptable 70-120% recoveries and < 25% RSD for 139-141 (82-83%) of the 169 diverse drug analytes spiked into powdered and liquid eggs, respectively, at three levels of regulatory interest. Qualitatively, rates of false positives and negatives were compared when applying three different regulatory identification criteria in which two or three MRMs/drug were used in each case. Independent of the identification criteria, rates of false positives remained <10% for 95-99% of the drugs whether 2 or 3 ions were monitored, but the percent of drugs with >10% false negatives decreased from 25-45 to 10-12% when using 2 vs. 3 MRMs/analyte, respectively. Use of a concentration threshold at 10% of the regulatory level as an identification criterion was also very useful to reduce rates of false positives independent of ion ratios. Based on these results, monitoring >2 ion transitions per analyte is advised when using MS/MS for analysis, independent of SANTE/12682/2019, FDA/USDA, or 2002/657/EC identification criteria. (Quant)identification results using all three criteria were similar, but the SANTE criteria were advantageous in their greater simplicity and practical ease of use.

Metabolomic Biomarkers Differentiate Soy Sauce Freshness under Conditions of Accelerated Storage

Naturally fermented soy sauce is one of the few globally valued food condiments. It is complex in its substrate, manufacturing processes, and chemical profile of salts and organic compounds, resulting from spontaneous, enzymatic and biochemical reactions. The overall chemical character of soy sauce has a few rivals relative to its chemical and bioactive complexity. Resulting from this complexity are unique sensory attributes contributing to the characteristic soy sauce flavor as well as potentiating other sensory sensations. Soy sauce is susceptible to deterioration after bottling during storage. This work examined soy sauces over an eight-month period using descriptive sensory methods and the discovery of metabolomic biomarkers with high resolution mass spectrometry, wherein samples were derivatized to enable volatility and identification of polar analytes. While several thousand metabolites were detected, only organic acids, amino acids, and various glycosylated metabolites were statistically defensible biomarkers of storage time. The relationships between sensory and metabolomic data were assessed using Kendall rank-based correlations to generate Kendall Tau correlation coefficients. A second approach filtered the data based on correlation significance and grouped molecules based on hierarchical clustering. Mass spectrometry analyses discovered several thousand unique analyte peaks with relevant changes denoted as significant relative to the fresh samples using volcano depictions of p values versus changes in compound abundances. We present a metabolomic approach for the analysis of complex food systems capable of differentiating a quantifiable extrinsic variable, which is, in this case, storage time with a correlation coefficient of 0.99. We further demonstrate that changes in soy sauce resulting from storage are characterized by sensory decreases in fruity/grape and nutty/sesame aroma and increases in methional/potato aroma and astringent attributes with concomitant changes in the concentrations of several key biomarkers.

Regional mineralogical and technological characterization of Cypriot Iron Age pottery: a view from Tel Dor

Excavations at Tel Dor, a Phoenician site on the northern coast of Israel, produced one of the most varied and best-stratified assemblages of Cypriot Iron Age ceramics ever found outside Cyprus. A long-term investigation of the nature of socio-economic liaisons between Dor and Cyprus, inter alia, by identifying through ceramic typology and petrography the specific Cypriot production centres that sent their products to Dor is currently in progress. This paper focuses on the analytical identification of production centres first suggested by macroscopic observations; temporal trajectories and cultural implications are addressed only preliminarily. The results indicate that the Cypriot vessels that reached Dor were only produced at Salamis, Kition, Amathus and Paphos, and that the vista of imports at Dor keeps changing throughout the period under consideration. This is the most comprehensive analytical study of Cypriot Iron Age ceramic fabrics to date. It has the potential to build a foundation for provenance studies of Cypriot Iron Age ceramic fabrics and the interconnections they embody. It is constrained, however, by the fact it was mainly production centres represented at Dor that were studied.

Coupling Miniaturized Free-Flow Electrophoresis to Mass Spectrometry via a Multi-Emitter ESI Interface.

We present a novel multi-emitter electrospray ionization (ESI) interface for the coupling of microfluidic free-flow electrophoresis (μFFE) with mass spectrometry (MS). The effluents of the μFFE outlets are analyzed in near real-time, allowing a direct optimization of the electrophoretic separation and an online monitoring of qualitative sample compositions. The short measurement time of just a few seconds for all outlets even enables a reasonable time-dependent monitoring. As a proof of concept, we employ the multi-emitter ESI interface for the continuous identification of analytes at 15 μFFE outlets via MS to optimize the μFFE separation of important players of cellular respiration in operando. The results indicate great potential of the presented system in downstream processing control, for example, for the monitoring and purification of products in continuous-flow microreactors.

Biomarkers for the diagnosis and management of heart failure: new frontiers

Heart failure (HF) has a complex pathophysiology including neurohormonal activation, inflammation and oxidative stress that, together with comorbidities, promote progressive myocardial damage and cardiac remodeling. Over the years the study of these pathogenic mechanisms has led to the identification of several analytes potentially useful as biomarkers in HF. High-sensitivity troponins and soluble suppression of tumorigenesis-2 are the most promising biomarkers for risk stratification of HF, with independent value to natriuretic peptides. Other biomarkers currently being evaluated as predictors of adverse outcome in HF are galectin-3, growth differentiation factor 15, mid-regional pro-adrenomedullin as well as makers of renal dysfunction. The use of multi-marker scores as well as the application of genomics, transcriptomics, proteomics and metabolomics could further refine the management of HF.

The Art of Hormone Measurements with Emphasis on Specificity Resulting in Diagnostic and Management Improvements

The Art of Hormone Measurements with Emphasis on Specificity Resulting in Diagnostic and Management Improvements