Frequency and type of adverse analytical findings in athletics: Differences among disciplines.

Athletics is a highly diverse sport that contains a set of disciplines grouped into jumps, throws, races of varying distances, and combined events. From a physiological standpoint, the physical capabilities linked to success are quite different among disciplines, with varying involvements of muscle strength, muscle power, and endurance. Thus, the use of banned substances in athletics might be dictated by physical dimensions of each discipline. Thus, the aim of this investigation was to analyse the number and distribution of adverse analytical findings per drug class in athletic disciplines. The data included in this investigation were gathered from the Anti-Doping Testing Figure Report made available by the World Anti-Doping Agency (from 2016 to 2018). Interestingly, there were no differences in the frequency of adverse findings (overall,~0.95%, range from 0.77 to 1.70%) among disciplines despite long distance runners having the highest number of samples analysed per year (~9812 samples/year). Sprinters and throwers presented abnormally high proportions of adverse analytical findings within the group of anabolic agents (p < 0.01); middle- and long-distance runners presented atypically high proportions of findings related to peptide hormones and growth factors (p < 0.01); racewalkers presented atypically high proportions of banned diuretics and masking agents (p = 0.05). These results suggest that the proportion of athletes that are using banned substances is similar among the different disciplines of athletics. However, there are substantial differences in the class of drugs more commonly used in each discipline. This information can be used to effectively enhance anti-doping testing protocols in athletics.

Orthogonal Comparison of Analytical Methods by Theoretical Reconstruction from Bottom-up Assay Data.

In the never-ending endeavor to produce stable and efficacious protein therapeutics, biopharmaceutical companies often employ numerous analytical techniques to characterize and quantify a drug candidate's stability. Mass spectrometry, due to the information-rich data it produces, is commonly used in its numerous configurations to ascertain chemical and structural stability. At issue is the comparison of the various configurations utilized, that is, comparing bottom-up methods such as proteolytic digest followed by reversed phase LC-MS with intact LC-MS methods. Similar issues also arise when using capillary isoelectric focusing to see how charge variants change over time, that is, monitoring the progression of charge altering modifications like deamidation. To this end, site-specific degradations as quantified from bottom-up methods like peptide mapping can be used to build reconstructions of both theoretical intact mass spectra as well as theoretical electropherograms. The result can then be superimposed over the experimental data to qualitatively, and perhaps quantitatively, evaluate differences. In theory, if both experimental bottom-up data and intact data are accurate, the theoretical reconstruction produced from the bottom-up data should perfectly overlay with that of the experimental data. Valuable secondary information can also be ascertained from reconstructions, such as whether modifications are stochastic, as well as a detailed view of all possible combinations of modifications and their quantities used in the reconstruction. This comparison is also useful in determining unknown mass differences in deconvoluted intact protein spectra that may be a result of multiple modifications in combination. The comparison of data from alternate sources provides a holistic and more comprehensive view of the molecule under study.

Microwave irradiation to the rapid extraction of Stryphnodendron adstringens (Barbatimão) compounds by statistical planning.

Stryphnodendron adstringens is a typical tree from Brazilian Savanah used in medicine as an anti-inflammatory and antiseptic agent. It is secondary metabolites has biological activities, so the development of efficient extraction methods is essential. Microwave irradiation through assisted extraction is innovative and highly efficient for bioactive compounds. The aim of this study was to optimize an extractive method for phenolics compounds, as tannins, from the stem bark of "barbatimão" by microwave irradiation using a statistical planning and to evaluate its consistency with conventional extraction. Microwave irradiation extraction, 16.36-22.12% of phenols and 15.91-18.69% of tannins, has a better yield when compared to conventional extraction, 14.99% of phenols and 16.70% of tannins. The method by microwave irradiation is consistent with the conventional one. However, extraction by microwave irradiation had a reduction in reaction time, reagent volume, samples amount and energy consumption when compared to conventional extraction.

The new IVD Regulation 2017/746: a case study at a large university hospital laboratory in Belgium demonstrates the need for clarification on the degrees of freedom laboratories have to use lab-developed tests to improve patient care.

Objectives: The new European In Vitro Diagnostic (IVD) Regulation 2017/746 (IVDR) restricts the use of lab-developed tests (LDT) after 26th May 2022. There are no data on the impact of the IVDR on laboratories in the European Union. Methods: Laboratory tests performed in UZ Leuven were divided in four groups: core laboratory, immunology, special chemistry, and molecular microbiology testing. Each test was classified as Conformité Européenne (CE)-IVD, modified/off-label CE-IVD, commercial Research Use Only (RUO) or LDT. Each matrix was considered a separate test. Results: We found that 97.6% of the more than 11.5 million results/year were generated with a CE-IVD method. Of the 922 different laboratory tests, however, only 41.8% were CE-IVD, 10.8% modified/off-label CE-IVD, 0.3% RUO, and 47.1% LDT. Off-label CE-IVD was mainly used to test alternative matrices not covered by the claim of the manufacturer (e.g., pleural or peritoneal fluid). LDTs were mainly used for special chemistry, flow cytometry, and molecular testing. Excluding flow cytometry, the main reasons for the use of 377 LDTs were lack of a CE-IVD method (71.9%), analytical requirements (14.3%), and the fact the LDT was in use before CE-IVD available (11.9%). Conclusions: While the large majority of results (97.6%) were generated with a CE-IVD method, only 41.8% of laboratory tests were CE-IVD. There is currently no alternative on the market for 71.5% of the 537 LDTs performed in our laboratory which do not fall within the scope of the current IVD directive (IVDD). Compliance with the IVDR will require a major investment of time and effort.

Voltammetric analysis for distinguishing portal hypertension-related from malignancy-related ascites: A proof of concept study.

BACKGROUND: Serum-ascites albumin gradient (SAAG) remains the most sensitive and specific marker for the differentiation of ascites due to portal hypertension from ascites due to other causes. SAAG has some limitations and may fail in selected conditions. Voltammetric analysis (VA) has been used for the detection of electroactive species of biological significance and has proven effective for detection infections in biological fluids. AIMS: In this study, we compared the accuracy of voltammetric analysis (VA) with that of SAAG to differentiate ascites due to portal hypertension from that having a different origin. METHODS: 80 ascites samples were obtained from patients undergoing paracentesis at the Campus Bio-Medico Hospital of Rome. VA was performed using the BIONOTE device. The ability of VA to discriminate ascitic fluid etiology and biochemical parameters was evaluated using Partial Least Square Discriminant Analysis (PLS-DA), with ten-fold cross-validations. RESULTS: Mean age was 68.6 years (SD 12.5), 58% were male. Ascites was secondary to only portal hypertension in 72.5% of cases (58 subjects) and it was secondary to a baseline neoplastic disease in 27.5% of cases (22 subjects). Compared to SAAG≥1.1, e-tongue predicted ascites from portal hypertension with a better accuracy (92.5% Vs 87.5%); sensitivity (98.3% Vs 94.8%); specificity (77.3% Vs 68.2%); predictive values (PPV 91.9% Vs 88.7% and NPV 94.4% Vs 83.3%). VA correctly classified ascites etiology in 57/58 (98.2%) of cases with portal hypertension and in 17/22 (77.2%) of cases with malignancy. Instead, VA showed poor predictive capacities towards total white blood count and polymorphonuclear cell count. CONCLUSIONS: According to this proof of concept study, VA qualifies as a promising low-cost and easy method to discriminate between ascites secondary to portal hypertension and ascites due to malignancy.

Developing New Criteria for Validity Evaluation of Analytical Methods.

Background: The appropriate validation of analytical methods has become an essential part of the determination of chemical substances. Invalid analytical methods lead to inaccurate data and misinterpretation of results in the pharmaceutical, food, and medical sciences. There are a number of guidelines issued on validation by international organizations. Some parameters have been proposed to evaluate the validity of an analytical method. They are accurate and comprehensive; however, proposing new criteria can help analysts to detect invalid methods. Objective: In this study, new criteria are proposed based on upper and lower limits of linear range and calculated responses by calibration curve equation. Methods: Further research on 150 reported analytical methods (non-separation-based and separation-based techniques) for chemicals and pharmaceuticals (organic and inorganic compounds) in scientific papers revealed that employing the coefficient of determination (R²) alone could lead analysts to an inaccurate linear range and method validation, and consequently, results showed that only 55% of these methods count as valid approaches. Conclusions: The established criteria based on the calibration curve equation and linear range appear to be applicable and suitable for validity evaluation of analytical methods.

Estimation of plant sampling uncertainty: an example based on chemical analysis of moss samples.

In order to estimate the level of uncertainty arising from sampling, 54 samples (primary and duplicate) of the moss species Pleurozium schreberi (Brid.) Mitt. were collected within three forested areas (Wierna Rzeka, Piaski, Poslowice Range) in the Holy Cross Mountains (south-central Poland). During the fieldwork, each primary sample composed of 8 to 10 increments (subsamples) was taken over an area of 10 m2 whereas duplicate samples were collected in the same way at a distance of 1-2 m. Subsequently, all samples were triple rinsed with deionized water, dried, milled, and digested (8 mL HNO3 (1:1) + 1 mL 30 % H2O2) in a closed microwave system Multiwave 3000. The prepared solutions were analyzed twice for Cu, Fe, Mn, and Zn using FAAS and GFAAS techniques. All datasets were checked for normality and for normally distributed elements (Cu from Piaski, Zn from Poslowice, Fe, Zn from Wierna Rzeka). The sampling uncertainty was computed with (i) classical ANOVA, (ii) classical RANOVA, (iii) modified RANOVA, and (iv) range statistics. For the remaining elements, the sampling uncertainty was calculated with traditional and/or modified RANOVA (if the amount of outliers did not exceed 10 %) or classical ANOVA after Box-Cox transformation (if the amount of outliers exceeded 10 %). The highest concentrations of all elements were found in moss samples from Piaski, whereas the sampling uncertainty calculated with different statistical methods ranged from 4.1 to 22 %.

Chemometrics and the identification of counterfeit medicines-A review.

This review article provides readers with a number of actual case studies dealing with verifying the authenticity of selected medicines supported by different chemometric approaches. In particular, a general data processing workflow is discussed with the major emphasis on the most frequently selected instrumental techniques to characterize drug samples and the chemometric methods being used to explore and/or model the analytical data. However, further discussion is limited to a situation in which the collected data describes two groups of drug samples - authentic ones and counterfeits.

Importance of implementing an analytical quality control system in a core laboratory.

INTRODUCTION: The aim of the clinical laboratory is to provide useful information for screening, diagnosis and monitoring of disease. The laboratory should ensure the quality of extra-analytical and analytical process, based on set criteria. To do this, it develops and implements a system of internal quality control, designed to detect errors, and compare its data with other laboratories, through external quality control. In this way it has a tool to detect the fulfillment of the objectives set, and in case of errors, allowing corrective actions to be made, and ensure the reliability of the results. OBJECTIVE: This article sets out to describe the design and implementation of an internal quality control protocol, as well as its periodical assessment intervals (6 months) to determine compliance with pre-determined specifications (Stockholm Consensus(1)). MATERIALS AND METHODS: A total of 40 biochemical and 15 immunochemical methods were evaluated using three different control materials. Next, a standard operation procedure was planned to develop a system of internal quality control that included calculating the error of the analytical process, setting quality specifications, and verifying compliance. RESULTS: The quality control data were then statistically depicted as means, standard deviations, and coefficients of variation, as well as systematic, random, and total errors. The quality specifications were then fixed and the operational rules to apply in the analytical process were calculated. Finally, our data were compared with those of other laboratories through an external quality assurance program. DISCUSSION: The development of an analytical quality control system is a highly structured process. This should be designed to detect errors that compromise the stability of the analytical process. The laboratory should review its quality indicators, systematic, random and total error at regular intervals, in order to ensure that they are meeting pre-determined specifications, and if not, apply the appropriate corrective actions.

Validating precision--how many measurements do we need?

BACKGROUND: A quantitative analytical method should be sufficiently precise, i.e. the imprecision measured as a standard deviation should be less than the numerical definition of the acceptable standard deviation. We propose that the entire 90% confidence interval for the true standard deviation shall lie below the numerical definition of the acceptable standard deviation in order to assure that the analytical method is sufficiently precise. We also present power function curves to ease the decision on the number of measurements to make. METHODS: Computer simulation was used to calculate the probability that the upper limit of the 90% confidence interval for the true standard deviation was equal to or exceeded the acceptable standard deviation. Power function curves were constructed for different scenarios. RESULTS: The probability of failure to assure that the method is sufficiently precise increases with decreasing number of measurements and with increasing standard deviation when the true standard deviation is well below the acceptable standard deviation. For instance, the probability of failure is 42% for a precision experiment of 40 repeated measurements in one analytical run and 7% for 100 repeated measurements, when the true standard deviation is 80% of the acceptable standard deviation. Compared to the CLSI guidelines, validating precision according to the proposed principle is more reliable, but demands considerably more measurements. CONCLUSIONS: Using power function curves may help when planning studies to validate precision.

The relationship between measurement uncertainty and reporting interval.

BACKGROUND: Measurement uncertainty (MU) estimates can be used by clinicians in result interpretation for diagnosis and monitoring and by laboratories in assessing assay fitness for use and analytical troubleshooting. However, MU is not routinely used to assess the appropriateness of the analyte reporting interval. We describe the relationship between MU and the analyte reporting interval. METHODS AND RESULTS: The reporting interval R is the smallest unit of measurement chosen for clinical reporting. When choosing the appropriate value for R, it is necessary that the reference change values and expanded MU values can be meaningfully calculated. Expanded MU provides the tighter criterion for defining an upper limit for R. This limit can be determined as R ≤ k·SDa/1.9, where SDa is the analytical standard deviation and k is the coverage factor (usually 2). CONCLUSION: Using MU estimates to determine the reporting interval for quantitative laboratory results ensures that reporting practices match local analytical performance and recognizes the inherent error of the measurement process.

Evaluation of analytical performance based on partial order methodology.

Classical measurements of performances are typically based on linear scales. However, in analytical chemistry a simple scale may be not sufficient to analyze the analytical performance appropriately. Here partial order methodology can be helpful. Within the context described here, partial order analysis can be seen as an ordinal analysis of data matrices, especially to simplify the relative comparisons of objects due to their data profile (the ordered set of values an object have). Hence, partial order methodology offers a unique possibility to evaluate analytical performance. In the present data as, e.g., provided by the laboratories through interlaboratory comparisons or proficiency testings is used as an illustrative example. However, the presented scheme is likewise applicable for comparison of analytical methods or simply as a tool for optimization of an analytical method. The methodology can be applied without presumptions or pretreatment of the analytical data provided in order to evaluate the analytical performance taking into account all indicators simultaneously and thus elucidating a "distance" from the true value. In the present illustrative example it is assumed that the laboratories analyze a given sample several times and subsequently report the mean value, the standard deviation and the skewness, which simultaneously are used for the evaluation of the analytical performance. The analyses lead to information concerning (1) a partial ordering of the laboratories, subsequently, (2) a "distance" to the Reference laboratory and (3) a classification due to the concept of "peculiar points".

[Survey of analytical works for drugs at emergency and critical care centers with high-performance instruments provided by the Ministry of Health and Welfare (at present: Ministry of Health, Labour, and Welfare) in fiscal 1998--continuation of survey with 2008 survey results as point of reference].

In a 2008 survey of the 73 emergency and critical care centers around the nation that were equipped with the drug and chemical analytical instrument provided by the Ministry of Welfare (currently the Ministry of Health, Labour, and Welfare) in 1998, 36 of those facilities were using the analytical instruments. Of these 36 facilities, a follow-up survey of the 17 facilities that recorded 50 or analyses per year. Responses were gained from 16 of the facilities and we learned that of those, 14 facilities (87.5%) were conducting analyses using the instrument. There was a positive mutual correlation between the annual number of cases of the 14 facilities conducting analyses with the instrument and the number of work hours. Depending on the instrument in use, average analytical instrument parts and maintenance expenses were roughly three million yen and consumables required a maximum three million yen for analysis of 51-200 cases per year. From this, we calculate that such expenses can be covered under the allowed budget for advanced emergency and critical care centers of 5,000 NHI points (1 point = 10 yen). We found there were few facilities using the instrument for all 15 of the toxic substances recommended for testing by the Japanese Society for Clinical Toxicology. There tended to be no use of the analytical instrument for compounds with no toxicology cases. However, flexible responses were noted at each facility in relation to frequently analyzed compounds. It is thought that a reevaluation of compounds subject to analysis is required.

Utilization of stat test priority in the clinical laboratory: a College of American Pathologists q-probes study of 52 institutions.

CONTEXT: Utilization of stat testing priority is a balance between safe, efficient patient management and resource expenditure. OBJECTIVE: To determine the rate of stat testing, compare rates among institutions, and determine the distribution of turnaround time expectations for different turnaround time priorities. DESIGN: During a 7-day period, participants prospectively determined the total number of chemistry, hematology, and coagulation billable tests from inpatients and emergency department patients. Among these, the total numbers of billable tests performed stat were identified. Laboratories also reported the levels of test priority they offered and turnaround expectations for each level of test priority. RESULTS: Fifty institutions submitted data for the study, with 2 additional participants submitting partial results. Participants identified 639 589 chemistry, hematology, and coagulation billable tests, with 229 896 (35.9%) performed stat. The stat rate varied from 21.3% at the 10th percentile to 55.4% at the 90th percentile, with a median of 37.0% of participants' tests performed stat. Laboratories include a mean of 206 tests in chemistry, hematology, and coagulation test menus, with 67% of these tests offered stat. The fraction of the test menu offered stat varied from 29.0% at the 10th percentile to 97.8% at the 90th percentile, with a median of 73.3% of tests on the menu offered stat. The most common number of testing priorities offered by participating laboratories was 3 (44.2%). CONCLUSIONS: Among the 52 participating laboratories, the median stat testing rate was 37.0% and a median 73.3% of the test menu was offered stat.

Metals in RDF and other high calorific value fractions from mechanical treatment of MSW: analysis and sampling errors.

RDF and other high calorific value fractions derived from MSW by mechanical treatment processes contain goods such as cans, cables, zippers or batteries which are highly concentrated in metals. The objective of this study was to investigate the importance of these metal carriers (i) for total metal loads and (ii) for sampling errors. Six different products derived from MSW were analysed for carrier bound and total loads of Al, Cd, Cr, Cu, Fe, Ni, Pb and Zn. Sophisticated sample preparation procedures were applied in order to quantify the separate analyte loads from metallic carriers. Typical values for total metal contents and shares of carrier bound loads were found as follows: Al, 20 g kg(-1) (30%); Cr, 0.4 g kg(-1) (50%); Cu, 5 g kg(-1) (80%); Fe, 40 g kg(-1) (80%); Ni, 0.15 g kg(-1) (70%); Pb, 0.4 g kg(-1) (40%); and Zn, 2 g kg(-1) (30%). NiCd-batteries were found in three materials representing 30-70 % of total Cd contents (total 6-20 mg kg(-1)). Sampling errors related to the distribution of analyte carriers were in most cases found in the range of 50-150 % relative standard deviation in spite of the large sample masses of 200-800 kg. The results demonstrate: (1) metal carriers are responsible for significant analyte loads; if they are not adequately considered, total metal contents may be severely underestimated; (2) sampling errors are dominated by the distribution of carriers; (3) correct analysis of total metal contents including loads from metallic components requires expensive sample preparation.

Risk analysis of analytical validations by probabilistic modification of FMEA.

Risk analysis is a valuable addition to validation of an analytical chemistry process, enabling not only detecting technical risks, but also risks related to human failures. Failure Mode and Effect Analysis (FMEA) can be applied, using a categorical risk scoring of the occurrence, detection and severity of failure modes, and calculating the Risk Priority Number (RPN) to select failure modes for correction. We propose a probabilistic modification of FMEA, replacing the categorical scoring of occurrence and detection by their estimated relative frequency and maintaining the categorical scoring of severity. In an example, the results of traditional FMEA of a Near Infrared (NIR) analytical procedure used for the screening of suspected counterfeited tablets are re-interpretated by this probabilistic modification of FMEA. Using this probabilistic modification of FMEA, the frequency of occurrence of undetected failure mode(s) can be estimated quantitatively, for each individual failure mode, for a set of failure modes, and the full analytical procedure.