Inter-day Variations Research Articles

Quantifying Sphingomyelin in Dairy through Infusion-Based Shotgun Mass Spectrometry with Lithium-Ion-Induced Fragmentation.

Quantifying sphingomyelin (SM) species by infusion-based mass spectrometry (MS) is complicated by the presence of isobaric phosphatidylcholine (PC) species, which generate a common m/z 184 product ion in the presence of ammonium ions as a result of the phosphocholine headgroup. Lithium ion adducts of SM undergo a selective dehydration [Li + H2O + (CH3)3NC2H4PO4] with a corresponding neutral loss of -207 Da. This neutral loss was employed to create a SM-selective method for identifying target species, which were quantitated using multiple reaction monitoring (MRM). SM-selective fragments in MS3 were used to characterize the sphingosine base and acyl chain. These methods were used to identify 50 individual SM species in bovine milk ranging from SM 28:1 to SM 44:2, with d16:1, d17:1, d18:1, d19:1, and d20:1 bases, and acyl fatty acids ranging from 10 to 25 carbons and 0-1 desaturations. Spiked SM standards into milk had a recovery of 99.7%, and endogenous milk SM had <10% coefficient of variation for both intra- and interday variability, with limits of detection of 1.4-5.55 nM and limits of quantitation of 11.8-178.1 nM. This MS-MRM method was employed to accurately and precisely quantify SM species in dairy products, including bovine-derived whole milk, half and half, whipping cream, and goat milk.

New HPLC pattern-oriented approach for quality control of enteric coated tablets containing aescin from Aesculus hippocastanum

From the seed of Aesculus hippocastanum L., a complex mixture of triterpene saponin glycosides known as aescin was isolated, purified and characterized to be an active pharmaceutical ingredient for preparing of drug products. A reversed phase high performance liquid chromatographic method with UV detection was developed for the determination of total triterpene glycosides in enteric coated tablets containing aescin in a pattern-oriented manner. The mobile phase consisted of a mixture of acetonitrile and 0.1 % phosphoric acid solution (40: 60). UV detection was performed at 220 nm. The chromatographic column was Gemini C18 column, 5 µm 250 mm × 4.6 mm, which was maintained at 25 ◦C, connected with a precolumn (C18, 4.0 × 3.0 mm, 5 µm). The linear range was from 53.4 to 160.1 μg·mL−1. The RSD of intra-and inter-day precision variations were less than 1 % and the mean recovery was (100.66 ± 0.49) % (RSD = 0.64 %). The method showed its suitability, simplicity, rapidity and precision. Accordingly, it was proven adequate for quality control of this herbal drug product either for registration with the regulartory authority or routine analysis.

Multiple bioanalytical method based residual biomass prediction in microbial culture using multivariate regression and artificial neural network

Optical density (OD) based measurements cannot be a reliable proxy for residual biomass concentration in polyhydroxyalkanoate (PHA) accumulating microbial culture, as cell size and morphology change during growth. In this study, four independent analytical methods i.e., OD measurement at 540 nm and 600 nm, tetrazolium reduction assay, and intracellular protein estimation were adopted to model residual biomass growth in Cupriavidus necator. The inter-day variation of calibration slope for residual biomass was significant (p < 0.001), and the regression coefficient (R2) of composite samples across the methods varied between 0.74 and 0.96. A reduced quadratic polynomial model (R2, 0.996; adjusted R2, 0.995, cross-validation R2 0.987) was chosen to predict residual biomass using multi-analytical measurements. Partial least square regression and variable selection suggested the inclusion of OD 540 nm and protein measurement into two retained latent variables, with R2 of 0.986, and adjusted R2 of 0.972. ANN model offered good predictability for residual biomass, showing close agreement of experimental and modelled datasets for training, validation, and test subsets with R2 of 0.998, 0.994, and 0.943, respectively. Analytical sensitivity of quadratic and PLS regression models were 0.058 and 0.164 respectively. A comparison of the proposed methods suggests that all three can be used as an alternative to dry-cell-weight-based residual biomass estimation, avoiding lengthy drying time and PHA extraction and measurement steps.

Development and Validation of a New Analytical HPLC-PDA Method for Simultaneous Determination of Cucurbitacins B and D from the Roots of Trichosanthes kirilowii

Trichosanthes kirilowii, one of the herbal formulas named SH003, has been used for treatment in traditional medicine. This paper aimed to analyze the marker compounds from the roots of T. kirilowii and evaluate a validation method for cucurbitacins B and D using high-performance liquid chromatography-photodiode array detector (HPLC-PDA). Two marker compounds were identified as cucurbitacin B (1) and cucurbitacin D (2) from the roots of T. kirilowii by spectroscopic analyses. Cucurbitacins B and D peaks were well separated and were detected at 15.4 min and 12.4 min, respectively, by a UV detector at 230 nm with the linearity (R2 &gt; 0.999) range between 5 and 250 μg/mL, limit of detections (LODs) were 1.87 μg/mL and 1.30 μg/mL, respectively, while limit of quantifications (LOQs) were 5.66 μg/mL and 3.93 μg/mL, respectively. The established method offered good precision with overall intra- and inter-day variations of 0.34–1.26 and 0.26–1.35%, respectively, for % relative standard deviation (RSD, acceptance limit %RSD &lt;3%). The cucurbitacins B and D recoveries ranged from 99.2 to 101.7% and 98.6 to 102.0%, respectively. These results suggest that cucurbitacins B and D could be a valuable candidate for marker compounds of the extract from T. kirilowii, and the proposed method was shown applicability for quality control of SH003.

The day-to-day temperature variability method as a tool for urban heat island analysis: A case of Zagreb-Grič Observatory (1887–2018)

The paper applies the relatively new day-to-day (DTD) method to analyse the day-to-day variability of minimum, mean and maximum daily air temperatures measured at the Zagreb Grič Observatory in the period from 1878 to 2018. The observatory is located in the centre of this rapidly developed city. The DTD values were calculated and compared for the whole year and for the warm period of the year (June 15th to September 15th). Neither positive nor negative trends in the time series of mean daily, DTDmean, and minimum daily, DTDTmin, day-to-day temperatures variabilities were found. There was a statistically significant difference in the behaviour of the series in the sub-period 1887–1958 and in the sub-period 1959–2018, when the maximum daily temperatures series, DTDTmax, and the difference between the maximum and minimum daily temperatures, ΔDTD, were considered. The DTD variabilities appeared in the annual series and those for the warm period of the year. Statistically lower inter-day variabilities were observed over the last 60 years. Variabilities in the warm period of the year, DTDTmin, are significantly lower than for the year as a whole. The variabilities in annual differences, ΔDTD, are significantly lower than those in the warm period of the year.

Trace determination of imidacloprid and its major metabolites in wheat-soil system.

Trace analysis method is a reliable basis for studying the translocation and metabolism of imidacloprid used as an insecticide in wheat, and it clarifies whether biologically active metabolites including residual imidacloprid, have long-lasting insecticidal potency against wheat aphids under seed treatment during the entire growth period. In this study, a highly sensitive analytical method was established to determine the residues of imidacloprid and its six metabolites (5-hydroxy imidacloprid, imidacloprid olefin, imidacloprid guanidine, imidacloprid urea, 6-chloronicotinic acid, and imidacloprid nitrosimine) in wheat-soil systems, such as in wheat leaves, wheat ears, wheat grains, roots, and soil. All the compounds were extracted using an ACN:water (8:2, v/v) mixture and purified by dispersive solid-phase extraction. The average recoveries ranged from 74.4% to 109.5% for all matrices, with intra- and inter-day variations of less than 14.9%. The limit of quantitation was in the range of 0.001-0.005 mg/kg. The method is demonstrated to be sensitive and accurate for monitoring imidacloprid and its metabolites at trace levels during the entire growth period under field conditions.

Comparison of electrospray and UniSpray™ ion sources with post-column hydrochloric acid infusion for 119 abuse relevant substances

Comparing the sensitivity of the Waters UniSpray™ ion source (USI) with the Waters electrospray ion source (ESI) on a Waters Xevo TQ-XS mass spectrometer with and without additional post-column infusion of low concentrated hydrochloric acid (HCl). To reduce sample volumes or increase analytical sensitivity for drugs of abuse detection in human body fluids, technological advances in mass spectrometry often target an increase in ionization efficiency. One example for this development is the USI, which claims higher ion yields and therefore higher sensitivity due to a unique geometry. Another possibility to increase sensitivity through increased ion yield is the post-column infusion of low concentrated HCl. For sensitivity comparison, we choose the, in our opinion, 119 most relevant medications and drugs of abuse. These were prepared in eleven acetonitrile solutions containing 10 analytes each and one with 9 analytes at a concentration of 1 μg/mL for each substance. For analysis, every solution was diluted 1:1000 in mobile phase A/ethylene glycol (70:30 v/v) to a concentration of 1.0 ng/mL. Solutions were analysed in triplicate on the same day interrupted by the ion source change, to decrease inter-day variations in sensitivity. Chromatographic separation was performed on a Waters 2.1 × 150 mm, 1.8 μm BEH Phenyl column kept at 60 °C on an Acquity UPLC connected to a Xevo TQ-XS detector (Waters). The standard ESI ion source or the USI ion source was mounted on the detector. Mobile phase A consisted of 20 mM ammonium formate and 0.1% formic acid (pH 3) and mobile phase B was 0.1% formic acid in methanol. Gradient elution was conducted within 6.0 min at a flow rate of 0.5 mL/min with 85% A and 15% B at the beginning and 100% B at the end. Data were acquired with the ion sources operating in the positive ionization MRM mode. Two transitions for each analyte were monitored at a constant dwell time of 10 ms over the full chromatographic run time. In an additional experiment, both ion sources were compared with additional post-column infusion of 0.0037% HCl at a flow rate of 5.0 μL/min. Injection volume was 2.0 μL in all experiments. USI provided a general gain in signal intensity (peak area): 12% ( n = 14) of the analytes showed a peak area increase up to 2-fold, 85% ( n = 101) increased between 2- and 4-fold and 3% ( n = 4) increased above 4-fold in peak area. Post-column HCl infusion with the ESI source mounted, resulted in an analyte dependent additional gain in signal intensity for 15% ( n = 18) of the analytes ranging from 2- to 21-fold. 78% ( n = 93) ranged from 0.8-fold to 2-fold. In contrast 7% ( n = 8) showed a signal decrease between 0.4-fold and 0.8-fold. The combination of USI and post-column HCl infusion resulted in an increase in peak area from 2-fold up to 62-fold compared to ESI without infusion for 91% (n = 108) of the analytes. 8% ( n = 9) where between 0.8-fold and 2-fold and 1% ( n = 2) ranged from 0.4-fold to 0.8-fold. With USI, a general improvement in analytical sensitivity under identical conditions could be achieved for all of our 119 “favorite analytes” separated in one chromatographic run. Additional post-column infusion of HCl increased sensitivity for many substances. This approach can be used very selectively when applied to certain retention time windows only. Further experiments are needed to understand how different adjustments of ESI and USI and different matrices will affect ionization. USI, especially in combination with post-column HCl infusion, is a promising tool to increase sensitivity in toxicological multi-target LC-MS/MS analysis.

New quantification method for monitoring 18 l-amino acids levels in schizophrenic patients by high-performance liquid chromatography coupled to tandem quadrupole mass spectrometer.

A fast, uncomplicated, sensitive and fully validated high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) method has been developed for estimating l-amino acids in the plasma of schizophrenic patients. The gradient-elution chromatographic method was implemented with the Luna® PFP column (50 ×2.0mm, 5 μm), and a mobile phase of 0.1% formic acid in water and methanol was used. The intra- and interday variability of the l-amino acids was <13.11%, their accuracy ranged from 85.14 to 116.75% at the quality control levels and the lower limit of quantification ranged from 2.5 to 15 nm. The extraction efficiency (apparent recovery) of amino acids from healthy plasma was employed by spiking the plasma with standard amino acids at the quality control levels. Their percentage recoveries ranged from 80.4 to 119.94%. Our method has a short run time and fast sample preparation compared with existing methods, which suffer from long preparative steps and/or time-consuming analysis, restricted reagents and the suboptimal performance characteristics of presently available technologies. Therefore, the proposed HPLC-MS/MS method was effectively applied for monitoring the l-amino acids in the plasma of schizophrenic patients and healthy volunteers.

Application of Parallel Reaction Monitoring to the Development and Validation of a Quantitative Assay for ST-246 in Human Plasma.

In this work, we developed and validated a robust and sensitive method of liquid chromatography with high-resolution mass spectrometry in parallel reaction monitoring (PRM) mode for ST-246 (tecovirimat) quantification in human blood plasma. The method was compared with the multiple reaction monitoring (MRM) technique and showed better selectivity and similar sensitivity in a wider concentration range (10–5000 ng/mL). Within this range, intra- and interday variability of precision and accuracy were within acceptable ranges in accordance with the European Medicines Agency guidelines, and recovery was 87.9–100.6%. Samples were stable at 4 °C within 48 h and at −20 °C up to 3 months. The recovery and matrix effects in the proposed HRMS method were about 5% higher than those reported for the MRM method, but the PRM method showed better accuracy with comparable precision. It was found that the ST-246 concentration shown by the PRM method is approximately 24% higher than the output of the MRM one. Nonetheless, the high selectivity with similar sensitivity, as compared with traditional MRM methods, makes the proposed approach attractive for research and clinical use.

Sticky Pi is a high-frequency smart trap that enables the study of insect circadian activity under natural conditions.

In the face of severe environmental crises that threaten insect biodiversity, new technologies are imperative to monitor both the identity and ecology of insect species. Traditionally, insect surveys rely on manual collection of traps, which provide abundance data but mask the large intra- and interday variations in insect activity, an important facet of their ecology. Although laboratory studies have shown that circadian processes are central to insects' biological functions, from feeding to reproduction, we lack the high-frequency monitoring tools to study insect circadian biology in the field. To address these issues, we developed the Sticky Pi, a novel, autonomous, open-source, insect trap that acquires images of sticky cards every 20 minutes. Using custom deep learning algorithms, we automatically and accurately scored where, when, and which insects were captured. First, we validated our device in controlled laboratory conditions with a classic chronobiological model organism, Drosophila melanogaster. Then, we deployed an array of Sticky Pis to the field to characterise the daily activity of an agricultural pest, Drosophila suzukii, and its parasitoid wasps. Finally, we demonstrate the wide scope of our smart trap by describing the sympatric arrangement of insect temporal niches in a community, without targeting particular taxa a priori. Together, the automatic identification and high sampling rate of our tool provide biologists with unique data that impacts research far beyond chronobiology, with applications to biodiversity monitoring and pest control as well as fundamental implications for phenology, behavioural ecology, and ecophysiology. We released the Sticky Pi project as an open community resource on https://doc.sticky-pi.com.

Identification and quantification of eight alkaloids in Aconitum heterophyllum using UHPLC‐DAD‐QTOF‐IMS: A valuable tool for quality control

Aconitum spp. are prime medicinal plants rich in alkaloids and have been used as the main constituents of traditional medicine in India and China. The whole plant can be toxic and creates pathophysiological conditions inside the human body. Therefore, simultaneous quantification of alkaloids within plant parts and herbal medicines associated with this genus is essential for quality control. We aimed to develop and validate methods using ultra-high-performance liquid chromatography-diode array detector-quadrupole time-of-flight ion mobility mass spectrometry (UHPLC-DAD-QTOF-IMS) and to develop an analytical strategy for the identification and quantification of alkaloid compounds (aconitine, hypaconitine, mesaconitine, aconine, benzoylmesaconitine, benzoylaconine, bulleyaconitine A, and deoxyaconitine) from Aconitum heterophyllum. We developed a simultaneous identification and quantification method for eight alkaloids using UHPLC-DAD-QTOF-IMS. The method was validated as per International Council for Harmonization of Technical Requirements for Pharmaceuticals for Human Use (ICH) guidelines and also in IMS mode. The developed method has good linearity (r2 = 0.997-0.999), LOD (0.63-8.31 μg/mL), LOQ (0.63-2.80 μg/mL), recovery (86.01-104.33%), reproducibility, intra- and inter-day variability (<3.25%), and stability. Significant qualitative and quantitative variations were found among different plant parts (flower, leaf, stem, root, and tuber) and five market products of A. heterophyllum. Furthermore, a total of 21 metabolites were also profiled based on the fragmentation pattern of MS2 using the validated method. An appropriate mobile phase using acetonitrile and water in a gradient elution gave a satisfactory chromatographic separation of eight Aconitum alkaloids with their adjacent peaks. Therefore, this method could provide a scientific and technical platform for quality control assurance.

Therapeutic Monitoring of Thiopurine Metabolites: Validation of an HPLC Method and Preliminary Findings from a Small Cohort of Malaysian Patients with Inflammatory Bowel Disease

Thiopurine therapy of inflammatory bowel disease (IBD) is guided by the relative blood concentrations 6-thioguanine nucleotides (6-TGN) and 6-methylmercaptopurine (6-MMP). However, their action is altered by in vivo phosphorylation, and this is not normally measured in clinical studies. Hence, we trialled a novel method for profiling phosphorylated thiopurine metabolites and revisited the association between thiopurine metabolites and IBD treatment outcomes. We first optimised and validated a published high-performance liquid chromatography (HPLC) method for measuring the blood levels of thioguanosine monophosphate (TGMP), thioguanosine diphosphate (TGDP), thioguanosine triphosphate (TGTP), and methylthioinosine monophosphate (MeTIMP). Then, we assembled a small cohort of IBD patients (n=20), who had been treated with azathioprine for at least three months, and obtained blood samples for analysis of the metabolites. The patients received treatments at the Universiti Kebangsaan Malaysia Specialist Centre between March 2018 and April 2019. They were classified as responders (n = 12) or non-responders (n = 6) to azathioprine based on their disease activity scores (CDAI or Mayo score). The HPLC method was precise with intraday and interday variation &lt; 15% for all the tested metabolites, and the relative accuracy ranged from 40.2 to 114.0%. We noted that the responders had higher median 6-TGN but lower median TGTP levels than the non-responders. However, the differences were not statistically significant (Wilcoxon rank-sum tests; 6-TGN, p = 0.925; TGTP, p = 0.189). The higher median 6-TGN level detected in the responders is in keeping with the findings of prior studies, suggesting that HPLC analysis of phosphorylated thiopurine metabolites is both technically feasible and clinically useful.

Online In-Tube Solid-Phase Microextraction Coupled with Liquid Chromatography-Tandem Mass Spectrometry for Automated Analysis of Four Sulfated Steroid Metabolites in Saliva Samples.

Accurate measurement of sulfated steroid metabolite concentrations can not only enable the elucidation of the mechanisms regulating steroid metabolism, but also lead to the diagnosis of various related diseases. The present study describes a simple and sensitive method for the simultaneous determination of four sulfated steroid metabolites in saliva, pregnenolone sulfate (PREGS), dehydroepiandrosterone sulfate (DHEAS), cortisol sulfate (CRTS), and 17β-estradiol-3-sulfate (E2S), by online coupling of in-tube solid-phase microextraction (IT-SPME) and stable isotope dilution liquid chromatography–tandem mass spectrometry (LC–MS/MS). These compounds were extracted and concentrated on Supel-Q PLOT capillary tubes by IT-SPME and separated and detected within 6 min by LC–MS/MS using an InertSustain swift C18 column and negative ion mode multiple reaction monitoring systems. These operations were fully automated by an online program. Calibration curves using their stable isotope-labeled internal standards showed good linearity in the range of 0.01–2 ng mL−1 for PREGS, DHEAS, and CRTS and of 0.05–10 ng mL−1 for E2S. The limits of detection (S/N = 3) of PREGS, DHEAS, CRTS, and E2S were 0.59, 0.30, 0.80, and 3.20 pg mL−1, respectively. Moreover, intraday and interday variations were lower than 11.1% (n = 5). The recoveries of these compounds from saliva samples were in the range of 86.6–112.9%. The developed method is highly sensitive and specific and can easily measure sulfated steroid metabolite concentrations in 50 μL saliva samples.

An application of the standardised reference extract quantification strategy in the quality control of ginseng infusions by liquid chromatography with mass spectrometric detection.

Limited availability of individual standards is a bottleneck for quality control of functional foods and natural medicines. The use of standard mixtures or secondary standards is a possible alternative in this case. Earlier, an approach known as standardised reference extract (RE) strategy was introduced for HPLC-UV analysis of different plant materials; however, its application in HPLC-MS analysis has not been investigated. To establish an HPLC-MS-based RE method for determination of ginsenoside content in ginseng infusions using commercially available extract reference material of Panax quinquefolius L. The developed HPLC-MS method was validated as precise (1.1%-9.4% intra-day variation; 1.6%-12.8% inter-day variation) and highly sensitive [limit of detection (LOD): 1-40 ng/mL; limit of quantification (LOQ): 4-120 ng/mL]. The stability of samples was satisfactory (5.7%-16.3%). The RE quantification method was compared with the external standard method, and the obtained difference was not significant, mostly in the range of 5%-10%. Matrix effects for the diluted samples of RE and ginseng infusions, determined via the standard addition method, were in the range of 85%-115% and 80%-126%, respectively, and were also positively correlated with the ginsenoside concentration. Eleven batches of ginseng infusions from different manufacturers were analysed using the established method. The method for HPLC-MS-based ginsenoside quantification using RE as a secondary standard was established for the first time. The results of this study demonstrate that the application of the standardised RE strategy in HPLC-MS can minimise the matrix effect-related error in addition to the cost-effective quality control of herbal products, foods, and traditional medicines.

MO639: Evaluation of Glycemic Control and Interday Glucose Variability Using Continuous Glucose Monitoring in Diabetic Hemodialysis Patients

Abstract BACKGROUND AND AIMS Continuous-glucose-monitoring (CGM) facilitates the assessment of interday glucose variability and identification of acute excursions of hyper- and hypoglycemia [1–4). METHOD Among 37 diabetic hemodialysis patients who underwent 7-day CGM with the iPRO2 device (Medtronic Diabetes, Northridge, CA, USA), we explored the accuracy of GA and hemoglobin A1c (HbA1c) in assessing glycemic control, using CGM-derived metrics as the reference standard. RESULTS In receiver-operating-characteristic (ROC) analysis, the area under the curve (AUC) in diagnosing a time in target glucose range of 70–180 mg/dL (TIR70-180) in &amp;lt;50% of readings was higher for GA {AUC 0.878; [95% confidence interval (CI)] 0.728–0.962} as compared with HbA1c [AUC 0.682 (95% CI 0.508–0.825)] (P &amp;lt; 0.01). The accuracy of GA [AUC 0.939 (95% CI 0.808–0.991)] in detecting a time above target glucose range &amp;gt;250 mg/dL (TAR &amp;gt;250) in &amp;gt;10% of readings did not differ from that of HbA1c [AUC 0.854 (95% CI 0.699–0.948)] (P = 0.16). GA [AUC 0.712 (95% CI 0.539–0.848)] and HbA1c [AUC 0.740 (95% CI 0.570–0.870)] had a similarly lower efficiency in detecting a time below target glucose range &amp;lt;70 mg/dL (TBR &amp;lt;70) in &amp;gt;1% of readings (P = 0.71). Although the mean glucose levels were similar, the coefficient of variation of glucose recordings (39.2% ± 17.3% versus 32.0% ± 7.8%, P &amp;lt; 0.001) and TBR &amp;lt;70 [median (range): 5.6% (0, 25.8) versus 2.8% (0, 17.9)] were higher during the dialysis-on than during the dialysis-off day. CONCLUSION The present diagnostic test study shows that among diabetic hemodialysis patients, GA had higher accuracy than HbA1c in detecting a 7-day CGM-derived TIR70-180 in &amp;lt;50% of readings. However, both GA and HbA1c provided an imprecise reflection of acute excursions of hypoglycemia and interday glucose variability.

MO376: Can the Urinary Albumin-Creatinine Ratio Be Calculated Over the Urinary Protein-Creatinine Ratio in Chronic Kidney Disease?

Abstract BACKGROUND AND AIMS Urine albumin-to-creatinine ratio (ACR) and protein-to-creatinine ratio (PCR) are used to measure urine protein. Recent guidelines recommend the use of the ACR, and equations have been developed incorporating ACR to predict risk of kidney failure. Where ACR cannot be measured, whether due to cost issues, laboratory inefficiencies, or other reasons, it is helpful to have a method for estimating ACR from PCR as accurately as possible. In this study, we investigated the usability of the formula developed by Keiichi Sumida et al.[1]. METHOD The formula for calculating the estimated ACR developed by Keiichi Sumida et al. includes urinary PCR, gender, diabetes, and hypertension variables. Between 2020 and 2021, eGFR, PCR, ACR and creatinine tests were requested from 644 patients who met the requirements for the formula and applied to Bakırköy Dr Sadi Konuk Training and Research Hospital Nephrology outpatient clinic. Estimated ACR value was calculated using the formula over PCR. With PCR and ACR measurement performed on the same day and from the same sample, intra-day and inter-day variation in excretion variability was minimized. eGFR values were evaluated in five subgroups as &amp;gt;90, between 60 and 89, between 30 and 59, 15 and 29 and &amp;lt;15, and the concordance between ACR and estimated ACR was examined for each group. PCR and ACR were analyzed by dye binding and immunoturbidimetric methods., and the relationship between estimated ACR and measured ACR was examined using the logarithmic-exponential function formula. NCSS (Number Cruncher Statistical System) 2007 (Kaysville, Utah, USA) program was used for statistical analysis. Descriptive statistical methods (mean, standard deviation, median, first quartile, third quartile, frequency, percentage, minimum and maximum) were used while evaluating the study data. Kruskal–Wallis test and Dunn–Bonferroni test were used for comparisons between groups of more than two quantitative variables that did not show normal distribution. Spearman correlation analysis was used to evaluate the relationships between quantitative variables. Statistical significance was accepted as P &amp;lt; 0.05. RESULTS It was conducted with a total of 644 cases, 49.2% (n = 317) male and 50.8% (n = 327) female. Of the subjects participating in the study, 44.4% had a diagnosis of hypertension and 28.7% had diabetes. PCR measurement values of the cases ranged from 7.5 to 5000 mg/g; the mean measurement value is 1048.29 ± 1166.77 mg/g. ACR measurement values of the subjects participating in the study ranged from 0.64 to 4799 mg/g; mean measurement value is 689.05 ± 891.20 mg/g. The estimated ACR measurement values of the cases ranged from 2 to 2843 mg/g; the mean measurement value is 487.87 ± 620.30 mg/g. When Intraclass Correlation Coefficient (ICC) levels were examined between estimated ACR and ACR measurements, the agreement at the level of 0.846 was found to be excellent (ICC = 0.846; P = 0.001; P &amp;lt; 0.01). In the groups with eGFR ≥90, 60–89, 30–59, 15–29 and &amp;lt;15; The agreement between estimated ACR and ACR measurements was excellent. (ICC = 0.793, 0.799,0.881,0.849, 0.883 P = 0.001; P &amp;lt; 0.01). CONCLUSION Urine ACR is the preferred measure of albuminuria; however, if ACR is not available or cannot be measured, ACR estimated from PCR can be helpful in CKD screening, staging, and prognosis.

Robustness of individualized inferences from longitudinal resting state EEG dynamics.

Tracking how individual human brains change over extended timescales is crucial to clinical scenarios ranging from stroke recovery to healthy aging. The use of resting state (RS) activity for tracking is a promising possibility. However, it is unresolved how a person's RS activity over time can be decoded to distinguish neurophysiological changes from confounding cognitive variability. Here, we develop a method to screen RS activity changes for these confounding effects by formulating it as a problem of change classification. We demonstrate a novel solution to change classification by linking individual-specific change to inter-individual differences. Individual RS-electroencephalography (EEG) was acquired over 5 consecutive days including task states devised to simulate the effects of inter-day cognitive variation. As inter-individual differences are shaped by neurophysiological differences, the inter-individual differences in RS activity on 1 day were analysed (using machine learning) to identify distinctive configurations in each individual's RS activity. Using this configuration as a decision rule, an individual could be re-identified from 2-s samples of the instantaneous oscillatory power spectrum acquired on a different day both from RS and confounded RS with a limited loss in accuracy. Importantly, the low loss in accuracy in cross-day versus same-day classification was achieved with classifiers that combined information from multiple frequency bands at channels across the scalp (with a concentration at characteristic fronto-central and occipital zones). Taken together, these findings support the technical feasibility of screening RS activity for confounding effects and the suitability of longitudinal RS for robust individualized inferences about neurophysiological change in health and disease.

Comprehensive quantitation of multi-signature peptides originating from casein for the discrimination of milk from eight different animal species using LC-HRMS with stable isotope labeled peptides

Milk species adulteration has become an altering issue worldwide. In this study, a robust quantification method based on LC-HRMS for the simultaneous detection and differentiation of milk type from eight different animal species (namely: cow, water buffalo, wild yak, goat, sheep, donkey, horse, and camel) was established by detecting nine signature peptides originating from casein. The developed method was in-house validated in terms of sensitivity, accuracy, and precision. As a result, limits of quantification (LOQ) were ranging from 5 to 30 µg/L, recoveries ranged from 95.2% to 104.5%, and intra-day and inter-day variability were lower than 11.4% and 12.6%, respectively, for all the targeted peptides. Furthermore, this method was successfully applied to 46 commercial minor species’ milk, in which 15 samples were false labeling. The obtained results indicate the necessity to monitor milk species adulteration in order to protect consumers from consuming misleading labeled minor species animal’s milk.

Pilot monitoring scheme of water pollutants in Important Bird and Biodiversity Areas

In this study we have established a monitoring scheme to determine the presence and distribution of widely used pharmaceuticals, pesticides, organophosphate esters (OPEs) and perfluoroalkyl substances (PFAS) in water bodies from Important Bird and Biodiversity Areas (IBAs) from Spain. The monitoring scheme included the georeferenced sampling of rocky mountain, Atlantic forest, riparian forest, Mediterranean forest, agricultural, inland aquatic and coastal aquatic IBAs, with the aim to evaluate the impact of widely used chemicals in those aquatic resources. Water samples were extracted using a generic solid-phase extraction protocol and analyzed by 3 analytical methods based on liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS). Quality parameters such as compound recovery, intra and inter-day variation, linearity and limits of detection were calculated in order to validate the methods. In addition, the ionization conditions and the optimization of the most appropriate transitions permitted unequivocal identification. Once the sampling and analytical procedure was set-up, 59 target compounds were monitored in 63 samples. Pharmaceutical, followed by pesticides, OPEs and PFAS were widespread along all IBAs studied at concentrations from 0.5 to 41083 ng/L. Overall, this study highlights the need to monitor the presence of contaminants in areas of high ecological interest to contribute to pollution control and mitigation towards protection of biodiversity.

A Method for the Analysis of Glyphosate, Aminomethylphosphonic Acid, and Glufosinate in Human Urine Using Liquid Chromatography-Tandem Mass Spectrometry.

The extensive use of herbicides, such as glyphosate and glufosinate, in crop production during recent decades has raised concerns about human exposure. Nevertheless, analysis of trace levels of these herbicides in human biospecimens has been challenging. Here, we describe a method for the determination of urinary glyphosate, its degradation product aminomethylphosphonic acid (AMPA), and glufosinate using liquid chromatography-tandem mass spectrometry (LC–MS/MS). The method was optimized using isotopically labelled internal standards (13C2, 15N-glyphosate, 13C, 15N, D2-AMPA, and D3-glufosinate) and solid-phase extraction (SPE) with cation-exchange and anion-exchange cartridges. The method provides excellent chromatographic retention, resolution and peak shape of target analytes without the need for strong acidic mobile phases and derivatization steps. The instrument linearity was in the range of 0.1–100 ng/mL, with R > 0.99 in the matrix for all analytes. The method detection limits (MDLs) and the method quantification limits (MQLs) were in the ranges of 0.12 (AMPA and glufosinate)–0.14 (glyphosate) ng/mL and 0.40 (AMPA)–0.48 (glyphosate) ng/mL, respectively. The recoveries of analytes spiked into urine matrix ranged from 79.1% to 119%, with coefficients of variation (CVs) of 4–10%. Repeated analysis of samples for over 2 weeks showed intra-day and inter-day analytical variations of 3.13–10.8% and 5.93–12.9%, respectively. The matrix effects for glyphosate, AMPA, and glufosinate spiked into urine matrix averaged −14.4%, 13.2%, and 22.2%, respectively. The method was further validated through the analysis of external quality assurance proficiency test (PT) urine samples. The method offers optimal sensitivity, accuracy, and precision for the urine-based assessment of human exposure to glyphosate, AMPA, and glufosinate.