A STATISTICAL APPROACH BASED ON THE TOTAL ERROR CONCEPT FOR VALIDATION THE BIOANALYTICAL METHOD: APPLICATION TO THE SPECTROPHOTOMETRIC DETERMINATION OF TRACES AMOUNT OF ACETAMINOPHEN IN HUMAN PLASMA

Objective: The use of the classical approach of analytical validation, in practice or in the literature, is common. However, statistical verification, that looks separately the two errors (such as bias and precision) to make a decision, presents a risk to declare that an analytical method is valid while it is not, or conversely. To minimize this risk, a new approach based on the concept of total error was proposed. Methods: This approach proposes a calculation the two sided tolerance interval by combining the two errors; bias and precision, in order to examine the validity of an analytical and bioanalytical method at each concentration level. In this paper, we aim to demonstrate the applicability and simplicity of the both methods based on the total error approach: accuracy profile and uncertainty profile. This study will be illustrated by validation case of a spectrophotometric method for the determination of trace amounts of acetaminophen in human plasma. Results: After the introduction of the correction coefficient which is worth 1.16, the results obtained with accuracy profile approach show clearly that the bioanalytical method is valid over a concentrations range of [100.34- 500] µg mL-1 since the upper and lower 90%-expectation tolerance limits have fallen within the two acceptance limits of ± 20%. The same results found using the uncertainty profile approach because the "two - sided 66.7%-content, 90% -confidence tolerance intervals "are found within two acceptance limits of ± 20% over the range of [170; 500] µm mL-1. Conclusion: The excellence of the total error approach was showen since it enables successfully to validate the analytical procedure as well the calculation of the measurement uncertainty at each concentration level

AN INNOVATIVE STRATEGY BASED ON UNCERTAINTY PROFILE FOR THE VALIDATION OF MICROBIOLOGICAL METHODS FOR COUNTING ENTEROBACTERIACEAE IN FOODS

Objective: A new and powerful statistical approach known as the uncertainty profile concept has been suggested for both testing the validity and making easy and straightforward interpretation of results obtained during the validation of an analytical method. The main goal of this paper is to confirm the applicability of this new strategy for the validation of a commercial kit, microbiological method, for the enumeration of the Enterobacteriaceae in foods and the estimate of the measurement uncertainty by using the newly provided formula and without referring to any additional experiments.Methods: An innovative formula to assess the uncertainty by using validation data and without recourse to other additional experiments was proposed. The uncertainty was evaluated through the two-sided β-content, γ-confidence tolerance interval, which is computed with three manners: the Mee's approach, the Generalized Pivotal Confidence, and the Modified Large Simple procedureResults: After the use of the three chemometric method of calculation of tolerance intervals, the obtained results with uncertainty profile show without doubt that the enumeration method is valid over the range of target values given that the upper and the lower 66.7 %-content, 90 %-confidence tolerance limits have fallen within the two acceptance limits of±0.25 Log unit. If the β is stretched to 80 %-content, 90 %-confidence, the three computed tolerance intervals lead to different decisions.Conclusion: we have demonstrated the ability of the uncertainty profile to be used for testing the validity of enumeration method which represents the first application of an uncertainty profile to food microbiological methods, and provides good estimations of the uncertainty measurements for each concentration level.Keywords: Validation, Uncertainty profile, β-content-γ-confidence tolerance interval, Uncertainty measurement, Microbiological metho

The synergic approach between machine learning, chemometrics, and NIR hyperspectral imagery for a real-time, reliable, and accurate prediction of mass loss in cement samples

Alternative and non-destructive analytical methods that predict analyte concentration accurately and immediately in a specific matrix are becoming vital in the analytical chemistry domain. Here, a new innovative and rapid method of predicting mass loss of cement samples based on a combination of Machine Learning (ML) and the emerging technique called Hyperspectral Imaging (HSI) is presented. The method has proved its reliability and accuracy by providing a predictive ML model, with satisfactory best validation scores recorded using partial least squared regression, with a reported ratio of performance to inter-quartile distance and root mean squared error of 12,89 and 0.337, respectively. Moreover, the possibility of optimizing and boosting the performance of the method by optimizing the predictive model performance has been suggested. Therefore, a features selection approach was conducted to disqualify non-relevant wavelengths and stress only relevant ones in order to make them the only contributors to a final optimized model. The best selected features subset was composed of 28 wavelengths out of 121, found by applying genetic algorithm combined to partial least squares regression as a feature selection method, on spectra preprocessed consecutively by the first-order savitzky-golay derivative calculated with 7-point quadratic SG filter, and multiplicative scatter correction method. The overall results show the possibility of combining HSI and ML for fast monitoring of water content in cement samples

Effect of Banana Waste Biochar on Physiological Responses and Growth of Seashore Paspalum

The current study aimed to evaluate the effect of banana waste biochar on the physiological traits and growth of Paspalum vaginatum under three water treatments (100%, 80%, and 60% of the water holding capacity (WHC) of the soil). A plastic pot experiment was done for the germination of paspalum vaginatum. The treatments were the addition of compost, banana waste biochar, or banana waste biochar and compost combination to the soil. We used multiple factor analysis (MFA) to reveal the relationship between the effect of banana waste biochar and the three water regimes on physiological data. The findings revealed that banana waste biochar had an important impacts on all traits under various water supply conditions. The photon yield of PSII of control treatment at three water regimes had the lowest response compared to amended treatments. Changes were observed in chlorophyll pigment among different treatments

Effect of Banana-Waste Biochar and Compost Mixtures on Growth Responses and Physiological Traits of Seashore Paspalum Subjected to Six Different Water Conditions

The effects of pyrolyzed agricultural waste generated from banana leaves on the development and physiological responses of Paspalum vaginatum in different water conditions were investigated. X-ray diffraction (XRD) and Fourier-transform infrared (FTIR) computations were utilized to describe the banana-waste biochar and determine the crystalline structure and functional groups. A plastic pot was used in two trials to examine the effectiveness of the studied biochar under two situations (well-watered Ww and limited-watered Lw). Seashore paspalum was cultivated in loam soil that had been modified with biochar as a single addition and a biochar compost mix. Six water scarcity scenarios were chosen (100, 80, 60, 25, 20, and 15% of water holding capacity (WHC) of the control soil). To analyze the varied responses of P. vaginatum in well-watered and limited-water environments, principal component analysis (PCA) was used. Under Ww, photosynthesis, biomass, fluorescence, and chlorophyll content increased, whereas, under Lw and control, they declined. Biochar and compost combinations enhanced the relative water content (RWC) more than biochar alone or in combination. Conversely, stomatal density in drought-stricken plants showed the reverse trend

Effect of Banana-Waste Biochar and Compost Mixtures on Growth Responses and Physiological Traits of Seashore Paspalum Subjected to Six Different Water Conditions

The effects of pyrolyzed agricultural waste generated from banana leaves on the development and physiological responses of Paspalum vaginatum in different water conditions were investigated. X-ray diffraction (XRD) and Fourier-transform infrared (FTIR) computations were utilized to describe the banana-waste biochar and determine the crystalline structure and functional groups. A plastic pot was used in two trials to examine the effectiveness of the studied biochar under two situations (well-watered Ww and limited-watered Lw). Seashore paspalum was cultivated in loam soil that had been modified with biochar as a single addition and a biochar compost mix. Six water scarcity scenarios were chosen (100, 80, 60, 25, 20, and 15% of water holding capacity (WHC) of the control soil). To analyze the varied responses of P. vaginatum in well-watered and limited-water environments, principal component analysis (PCA) was used. Under Ww, photosynthesis, biomass, fluorescence, and chlorophyll content increased, whereas, under Lw and control, they declined. Biochar and compost combinations enhanced the relative water content (RWC) more than biochar alone or in combination. Conversely, stomatal density in drought-stricken plants showed the reverse trend

Limiting the Hurtful Oxidative Stress and Seasonal Physiological Adaptations in Seashore Paspalum through the Use of Banana Waste Biochar and Compost Mixtures

The study’s purpose was to reduce the oxidative stress, seasonal physiological changes of paspalum vaginatum and ameliorate soil properties through the addition of banana waste biochar and compost. Different rates of organic amendments were incorporated into sandy loam soil to investigate their impact on paspalum physiological, biochemical, and development in pot and field settings over three seasons (winter, spring and summer). Under the conditions of these two places, paspalum leaves gas exchange characteristics, stomatal traits, anatomy traits, relative water content, proline, antioxidant enzyme activities, and paspalum pigments were determined. For the irrigation system, two rates were chosen: 20% and 60% of the water holding capacity of the control plot WHC. In this study, two advanced statistical analyses were conducted. A factor analysis of mixed data (FAMD) was performed for the analysis of the effect of our charcoal on soil data. Meanwhile, the impact of banana waste biochar on biological activities was investigated using multiple factorial analysis (MFA). The use of biochar and compost blends boosted the cation exchange capacity (CEC) of treated soils, according to our findings. Furthermore, the use of banana waste biochar improved biological basis in the summer season compared with previous seasons. Different antioxidant capacities in seashore paspalum were boosted in the improved soils compared to the untreated ones

Biological, Physico-Chemical and Morphological Analyses of Four Biochars Derived from Agricultural Waste

Around the world, the increasing population and consumption are placing huge demands on food. Agriculture is considered one of the important sectors in the world and the force to feed humanity. While under these circumstances, which stand out by successive years of drought, degradation of soil, climate change, and global warming, this sector has multifaceted a major issue that goes beyond threatening food security. Thus, Morocco characterized by an arid and semi-arid climate is one example of countries that suffered from those problems. Due to lack of rain, the water resources of some Moroccan arable lands are consumed highly as well as the quality of its soils is now degraded. This issue calls for new approaches to amending the degraded soils in these regions and sustain water supplies. Indeed, biochar can be a remedy for these poor soils; in fact, it has an incredible sequester carbon on soil, a benefit on the environment as well as on plant growth. Despite its virtues, certain biochars contain phytotoxic compounds. In this study, four biochars prepared from banana waste, peanut hull, almond shells, and walnut shells were tested on three plant species (cress to test (HAP), barley for assessing heavy metals, and lettuce to assess salinity) before any field application. The chemical and physical analysis was done for the four biochars and the sandy soil, the four biochars were also analyzed by scanning electron microscopy (SEM) for identifying the morphology of each biochar. The results showed that the four biochars enhanced water holding capacity (WHC), they also revealed the existence of heavy metals especially for almond shells biochar and walnut shells biochar. While for the morphology of each biochar, banana waste biochar (BC-BW) and peanut hull biochar (BC-PeH) had more pores than almond shells biochar (BC-Alm) and walnut shells biochar(BC-WS). Concerning the phytotoxic tests, the lettuce was germinated in all biochars treatments except for the 8% biochar banana treatment, for the cress and barley, all the treatments were grown

QSAR modeling, molecular docking and molecular dynamic simulation of phosphorus-substituted quinoline derivatives as topoisomerase I inhibitors

As they facilitate the cleavage of single and double stranded DNA to relax supercoils, unwind catenanes, and condense chromosomes in eukaryotic cells, Topoisomerase plays crucial roles in cellular reproduction and DNA organization. Because the unrepaired single and double stranded DNA breaks these complexes generate might result in apoptosis and cell death, they are cytotoxic agents.In this study, 28 compounds derived from phosphorus-substituted quinoline are subjected to a quantitative structure–activity relationship (QSAR) using partial least squares, principal component regression, and multiple linear regression. The Gaussian 09 software and the Molecular Operating Environment program were used to calculate molecular descriptors. The anti-proliferative activity was correlated with a variety of electronic and structural characteristics of the molecules, such as EHOMO (energy of the highest occupied molecular orbital) and ELUMO (energy of the lowest unoccupied molecular orbital), which provided evidence for the modeling. The B3LYP/6-31G (d, p) level of theory's Density Functional Theory (DFT) approach was used to compute these electronic properties, and Principal Component Analysis (PCA) was used to test for collinearity between the descriptors. In fact, three alternative prediction models were created using various 2D and 3D descriptor counts, and they were each assessed using the statistical metrics of coefficient of determination (R2) and root mean squared error (RMSE). A MLR model had the best predictive performance of all the constructed models, as indicated by R2 and RMSE of 0.865 and 0.316, respectively.Three proteins (6G77, 2NS2, and 5K47) for lung, ovarian, and kidney malignancies showed strong binding affinities via hydrophobic interactions and H-bonds with the pertinent chemicals by crystal structure modeling. Compounds C11, C19 and C26, respectively, showed the highest binding energy for ovarian, kidney and lung cancer. The outcomes of the molecular dynamic MD simulation diagram were produced to support the molecular docking findings from earlier research, which demonstrated that inhibitors were stable in the active sites of the selected proteins for 10 ns. This raises the possibility that these chemicals could serve as a valuable model for the development and synthesis of more effective anticancer prospects