Mispa count X; The first indigenous indian hematology 3-part analyzer

: Impedance technology was a revolution in the history of Hematology. Mispa Count X is the first indigenous 3-part hematology analyzer in India, which works on the principle of impedance technology. : Performance evaluation of Mispa Count X.: The analyzer produces the measurement results of 18 parameters with throughput of 60 samples per hour. Mispa Count X was compared with benchmark analyzers Coulter DxH 800 and Sysmex XN 1000 to validate its performance. : Mispa Count X exhibited a wide linearity range for WBC, RBC, platelet and hemoglobin. The carry over for WBC, RBC, PLT and Hb was estimated and found to be well within the acceptable limits. The r values (> 0.90) and bias estimation of Mispa Count X on comparing with Coulter DxH 800 and Sysmex XN 1000 were acceptable, except for mid cell counts and for MPV. Mispa Count X exhibited good precision with an acceptable CV% (< 10%). The primary parameters of the stored samples were stable at room temperature for 24 hours. : So we conclude our study by proving that the Mispa Count X would be an affordable-reliable alternative for Indian healthcare sector instead of expensive imported hematology analyzers.

METHOD VALIDATION OF SIMVASTATIN IN PCL-PEG-PCL TRIBLOCK COPOLYMER MICELLES USING UV-VIS SPECTROPHOTOMETRIC FOR SOLUBILITY ENHANCEMENT ASSAY

Objective: This study aims to increase the solubility of simvastatin (SIM), a hydrophobic drug, by incorporating it into PCL-PEG-PCL triblock copolymer micelles and validating the assay method used, namely Uv-Vis spectrophotometric. Methods: The shake flask method was used to determine the increase in solubility experienced by SIM after being incorporated into the micellar system. The values ​​of maximum wavelength (λmax), linearity, LOD, LOQ, accuracy, and precision were used as parameters measured to assess the validity of the assay method used. Results: The results showed that PCL-PEG-PCL triblock copolymer micelles could increase SIM solubility by 9.7 times (89.49±5.75 µg/ml) compared to SIM without modification (9.19±0.24 µg/ml). The validation results show the λmax value of 239 nm, a linear calibration curve with an R-value of 0.9994, LOD and LOQ of 0.33 µg/ml and 1.00 µg/ml, accurate measurement with recovery at concentrations of 80%, 100%, and 120% were 102.93±1.32%, 100.78±0.40%, and 104.58±0.79% and also had good precision ​​with RSD<2%. Conclusion: The PCL-PEG-PCL triblock copolymer micelles can increase SIM solubility and the Uv-Vis spectrophotometric method has been validated successfully for the quantitative analysis of SIM in PCL-PEG-PCL triblock copolymer micelles.

Fast Dispersive Liquid-Liquid Microextraction Based on Temperature Switching Deep Eutectic Solvent as A Green Extractant

With the development of research, it was found that the dispersive liquid-liquid microextraction (DLLME) was limited by the tedious extraction process and toxic extractant. A thermo-switchable deep eutectic solvent (DES) was applied to the DLLME as a green extractant in this paper. The DES can be dispersed and aggregated by shaking and heating in the water during the extraction process due to the surfactant and thermo-switchable properties, which shortened the extraction time as low as 5 minutes. The feasibility of the developed method was verified using 4 organophosphorus pesticides and 5 pyrethroids as targets in simulated water samples, which showed good precision (RSD%, 0.8-9.7, n=3) and low detection limit (0.16-0.81 µg L−1, S/N = 3) under the optimal extraction conditions. This method was used to detect the pesticide content in four natural rivers in Xi'an, and the recoveries of these spiked samples at three concentrations levels were among 81–113%. This is the first time to combine the toxic-free and thermo-switchable properties of DES in DLLME to proposes a simple, fast, effective, and green pretreatment method.

M-N interaction curves for rectangular concrete-filled steel tube columns subjected to uniaxial bending moments

abstract: In this paper, a computational code was developed to obtain M-N interaction curves for rectangular concrete-filled steel tube columns considering the strain compatibility in the cross-section. Considering the composite section subjected to uniaxial bending moments, expressions were developed to determine normal force, moment resistance, neutral axis depth and components resistance of cross-section. Such expressions were implemented in a computational tool developed to the authors and that allows to obtain the M-N pairs of strength. The steel and concrete ultimate strains were defined with the aid of the Brazilian standard for reinforced concrete structures ABNT NBR 6118. The obtained results were compared to simplified curves defined according to the theoretical models of ABNT NBR 8800, ABNT NBR 16239, EN 1994-1-1 and literature data. The proposed model showed good agreement with literature results and had good precision to estimate the ultimate moment values. To further understand the resistance of composite columns under uniaxial bending moments, parametric study was performed to evaluate the influence of the compressive strength of concrete, yielding strength of steel and steel area ratio on M-N interaction curves. The results indicate that the yielding strength of steel and the steel area ratio were the variables that most influenced the values of composite columns resistance (normal force and bending moment).

Electrochemical Sensor for Methamphetamine Detection Using Laser-Induced Porous Graphene Electrode

A 3D porous graphene structure was directly induced by CO2 laser from the surface of Kapton tape (carbon source) supported by polyethylene terephthalate (PET) laminating film. A highly flexible laser-induced porous graphene (LI-PGr) electrode was then fabricated via a facile one-step method without reagent and solvent in a procedure that required no stencil mask. The method makes pattern design easy, and production cost-effective and scalable. We investigated the performance of the LI-PGr electrode for the detection of methamphetamine (MA) on household surfaces and in biological fluids. The material properties and morphology of LI-PGr were analysed by scanning electron microscopy (SEM), energy dispersive x-ray (EDX) and Raman spectroscopy. The LI-PGr electrode was used as the detector in a portable electrochemical sensor, which exhibited a linear range from 1.00 to 30.0 µg mL−1 and a detection limit of 0.31 µg mL−1. Reproducibility was good (relative standard deviation of 2.50% at 10.0 µg mL−1; n = 10) and anti-interference was excellent. The sensor showed good precision and successfully determined MA on household surfaces and in saliva samples.

An evaluation of the performance of the Point of Care Test iCHROMA™ AFP method: Precision and accuracy

The estimation of serum alpha-fetoprotein (AFP) is useful in the diagnosis and monitoring of primary hepatocellular carcinoma, hepatoblastoma, non-seminomatous testicular germ cell tumours and other germ cell tumours. The iCHROMA™ AFP is a lateral flow chromatography, fluorescence immunoassay (FIA) for the quantitative determination of AFP in serum or plasma. In this study, the Boditech iCHROMA™ AFP assay had a very good precision of 9.8%. It showed a very good correlation with the following 12 methods: Abbott Architect (r2 = 0.9705), BioMerieux VIDAS (r2 = 0.9717), Roche Cobas 6000/8000 (r2 = 0.9738), Siemens Centaur XP/XPT/Classic (r2 = 0.9654), Siemens/DPC/Immulite 2000/2500 (r2 = 0.9673), Siemens/DPC/Immulite 1000 (r2 = 0.9670), Beckman Dxl 600/800 (r2 = 0.9676), Roche Elecsys (r2 = 0.9683), Roche Cobas 4000/e411 (r2 = 0.9688), Roche Modular E170 (r2 = 0.9692), SNIBE Maglumi (r2 = 0.9457) and Ortho Vitros 3600/5600/ECi (r2 = 0.9714). In summary, the iCHROMA™ AFP, a rapid point of care test method, has a within-run precision value of less than 10% and excellent correlations with traditional laboratory methods. There is a consistent overestimation with the iCHROMA™ method, which must be taken into consideration when setting a reference range.

Performance Evaluation of the KRYPTOR Compact PLUS Analyzer-Based B.R.A.H.M.S. CgA Ⅱ KRYPTOR Assay for Chromogranin A Measurement

Numerous immunoassays have been developed to measure the levels of chromogranin A (CgA), a useful biomarker for diagnosing and monitoring generally heterogeneous neuroendocrine tumors (NETs). Here, we evaluated the imprecision and linearity of three such assays: KRYPTOR (ThermoFisher Scientific), NEOLISA (EuroDiagnostica), and CgA-RIA (CisBio), using 123 samples for each assay. The correlation coefficients between the assays were 0.932 (CgA-RIA versus NEOLISA), 0.956 (KRYPTOR versus CgA-RIA), and 0.873 (NEOLISA versus KRYPTOR). KRYPTOR showed good precision, with percent coefficients of variation less than 5% for low and high concentration quality controls. Linearity was maintained over a wide concentration range. Comparison of CgA levels from three disease entities (NETs, non-NET pancreatic tumors, and prostate cancer) and healthy controls showed that patients with NETs had significantly higher CgA levels (n = 57, mean: 1.82 ± 0.43 log ng/mL) than healthy individuals (n = 20, mean: 1.51 ± 0.23 log ng/mL; p = 0.018). No other significant differences between groups were observed. All three immunoassays showed strong correlations in measured CgA levels. Because KRYPTOR operation uses a fully automated random-access system and requires shorter incubation times and smaller sample volumes, the KRYPTOR assay may improve laboratory workflow while maintaining satisfactory analytical performance.

Parameter N Analysis on the Rational-Talbot Algorithm for Numerical Inversion of Laplace Transform

This article investigates the numerical inversion of the Laplace Transform by the Rational-Talbot method and analyzes the influence on the variation of the free parameter N established by the technique when applied to certain functions. The set of elementary functions, for which the method is tested, has exponential and oscillatory characteristics. Based on the results obtained, it was concluded that the Rational-Talbot method is e cient for the inversion of decreasing exponential functions. At the same time, to perform the inversion process effectively for trigonometric forms, the algorithm requires a greater amount of terms in the sum. For higher values of N, the technique works well. In fact, this is observed in inverting the functions transform, that combine trigonometric and polynomial factors. The method numerical results have a good precision for the treatment of decreasing exponential functions when multiplied by trigonometric functions.

Novel Machine Learning for Human Actions Classification Using Histogram of Oriented Gradients and Sparse Representation

Recognition of human actions is a trending research topic as it can be used for crucial medical applications like life care and healthcare. In this research, we propose a novel machine learning algorithm for the classification of human actions based on sparse representation theory. In the proposed framework, the input videos are initially partitioned into several temporal segments of a predefined length. From these temporal segments, the key-cuboids are then obtained. These cuboids are obtained based on the locations having maximum variation in orientation. From these regions, key-cuboids are extracted. From the key-cuboids, Histogram of Oriented Gradient (HOG) features are extracted. This new descriptor has the capability to express the dynamic features in the action videos. Using these features, a single shared dictionary is created from the videos belonging to different classes using K-Singular Value Decomposition (K-SVD) algorithm. This dictionary has the combined features of all the action classes. This shared dictionary is generated during the training phase. During the testing phase, the features belonging to a test class is classified using a novel Sparse Representation Modeling based Action Recognition (SRMAR) Algorithm using Orthogonal Matching Pursuit (OMP) and the shared dictionary. The proposed framework was evaluated using popular benchmark action recognition datasets like KTH dataset, Olympic dataset and the Hollywood dataset. The results obtained using these datasets were represented in the form of a confusion matrix. Evaluation was performed using metrics like overall classification accuracy, specificity, precision, recall and F-score that were obtained from the confusion matrix. This system achieved a high specificity of about 99.52%, 99.16% and 96.15% for the KTH dataset, Olympic dataset and the Hollywood datasets, respectively. Similarly, the proposed framework attained very good precision of 97.64%, 90.46% and 73.39% for the KTH dataset, Olympic dataset and the Hollywood datasets, respectively. Also, the average value of recall achieved was 97.58%, 90.86% and 74.09% for the KTH dataset, Olympic dataset and the Hollywood datasets, respectively. It was also observed that the proposed machine learning algorithm achieved outstanding results compared to the existing state-of-the-art human action recognition frameworks in the literature.

The ability of a submaximal cycle ergometer test to detect longitudinal changes in VO2max

Background The purpose of the present study was to examine the ability of a submaximal cycling test to detect longitudinal changes in maximal oxygen uptake (VO2max) and examine the conformity between changes in measured and estimated VO2max over a time span of 5–8 years. Methods A total of 35 participants (21 men and 14 women), aged 29 to 63 years, performed the Ekblom-Bak (EB) submaximal cycle test for estimation of VO2max and a maximal treadmill running test for direct measurement of VO2max. The baseline tests were conducted between 2009 and 2012, and the follow-up tests were completed 5 to 8 years later. Pearson’s coefficient of correlation (r) and paired sample t-test were used to analyse the association between change in measured and estimated VO2max. Random and systematic errors between the measured and estimated VO2max were evaluated using Bland-Altman plots. Repeated measures ANOVA were used to test differences between changes over time. Results There was no significant change in mean measured VO2max between baseline and follow-up (p = 0.91), however large individual variations were noted (− 0.78 to 0.61 L/min). The correlation between individual change in measured and estimated VO2max was r = 0.75 (p < 0.05), and the unstandardised B-coefficient from linear regression modelling was 0.88 (95% CI 0.61 to 1.15), i.e., for each litre of change in estimated VO2max, the measured value had changed 0.88 L. The correlation between baseline and follow-up errors (the difference between estimated-measured VO2max at each occasion) was r = 0.84 (p < 0.05). With regard to the testing procedure, repeated measures ANOVA revealed that there was no significant difference between the group who exercised at the same work rates at baseline and follow-up (n = 25), and those who required a change in work rate (n = 10). Conclusions The EB test detected a change in VO2max with reasonably good precision over a time span of 5–8 years. Further studies are needed to evaluate if the test can be used in clinical populations and in subjects with different medications.