Comparison Of Methods Research Articles

Assessment of volume flow rate in arteriovenous fistulas with a novel ultrasound Doppler device (earlybird): Trend analysis, comparison of methods, and inter- and intra-rater reliability.

An accessible tool is required to analyze volume flow trends in arteriovenous fistulas for hemodialysis. Earlybird, an easy-to-place ultrasound Doppler device, has shown comparable accuracy to duplex ultrasound. In this study, we compared volume flow measurements obtained with duplex ultrasound and the dilution technique to an enhanced earlybird device, featuring a dual Doppler probe system, eliminating the requirement for a known insonation angle. Nine patients with a distal radiocephalic arteriovenous fistula were monitored for 12 months with regular volume flow measurements. Correlation and inter- and intra-class reliability analyses were conducted. An overall moderate correlation was observed between earlybird and duplex ultrasound or dilution technique (intraclass correlation coefficient = 0.606 (95% confidence interval 0.064, 0.721) and 0.581 (0.039, 0.739), respectively). Duplex ultrasound compared to dilution measurements, demonstrated an overall moderate correlation (0.725 (0.219, 0.843)). Correlation between earlybird and duplex ultrasound was stronger for the arteriovenous fistula (0.778 (0.016, 0.901)) than the brachial artery (0.381 (-0.062, 0.461)). For earlybird, inter-rater reliability was excellent for the arteriovenous fistula (0.907 (0.423, 0.930)) and poor for the brachial artery (0.430 (0.241, 0.716)). Duplex ultrasound showed a good inter-rater reliability (arteriovenous fistula: 0.843 (0.610, 0.871), brachial artery: 0.819 (0.477, 0.864)). The overall intra-rater reliability was good for duplex ultrasound (rater A: 0.893 (0.727, 0.911); rater B: 0.853 (0.710, 0.891)), while excellent for earlybird (rater A: 0.905 (0.819, 0.928); rater B: 0.921 (0.632, 0.969)). We observed a weaker correlation in the measurements of volume flow rates in arteriovenous fistulas when obtained using earlybird compared to dilution technique, unlike the comparison between duplex ultrasound and the dilution technique. However, inter-rater reliability for the arteriovenous fistula was excellent with earlybird and good with duplex ultrasound, indicating the potential of earlybird as a tool for frequent measurements, enabling trend surveillance and predicting adverse outcomes.

Comparison of a quasi Newton method using Broyden’s update formula and an adjoint method for determining local magnetic material properties of electrical steel sheets

Purpose Performing accurate numerical simulations of electrical drives, the precise knowledge of the local magnetic material properties is of utmost importance. Due to the various manufacturing steps, e.g. heat treatment or cutting techniques, the magnetic material properties can strongly vary locally, and the assumption of homogenized global material parameters is no longer feasible. This paper aims to present the general methodology and two different solution strategies for determining the local magnetic material properties using reference and simulation data. Design/methodology/approach The general methodology combines methods based on measurement, numerical simulation and solving an inverse problem. Therefore, a sensor-actuator system is used to characterize electrical steel sheets locally. Based on the measurement data and results from the finite element simulation, the inverse problem is solved with two different solution strategies. The first one is a quasi Newton method (QNM) using Broyden's update formula to approximate the Jacobian and the second is an adjoint method. For comparison of both methods regarding convergence and efficiency, an artificial example with a linear material model is considered. Findings The QNM and the adjoint method show similar convergence behavior for two different cutting-edge effects. Furthermore, considering a priori information improved the convergence rate. However, no impact on the stability and the remaining error is observed. Originality/value The presented methodology enables a fast and simple determination of the local magnetic material properties of electrical steel sheets without the need for a large number of samples or special preparation procedures.

BERNN: Enhancing classification of Liquid Chromatography Mass Spectrometry data with batch effect removal neural networks

Liquid Chromatography Mass Spectrometry (LC-MS) is a powerful method for profiling complex biological samples. However, batch effects typically arise from differences in sample processing protocols, experimental conditions, and data acquisition techniques, significantly impacting the interpretability of results. Correcting batch effects is crucial for the reproducibility of omics research, but current methods are not optimal for the removal of batch effects without compressing the genuine biological variation under study. We propose a suite of Batch Effect Removal Neural Networks (BERNN) to remove batch effects in large LC-MS experiments, with the goal of maximizing sample classification performance between conditions. More importantly, these models must efficiently generalize in batches not seen during training. A comparison of batch effect correction methods across five diverse datasets demonstrated that BERNN models consistently showed the strongest sample classification performance. However, the model producing the greatest classification improvements did not always perform best in terms of batch effect removal. Finally, we show that the overcorrection of batch effects resulted in the loss of some essential biological variability. These findings highlight the importance of balancing batch effect removal while preserving valuable biological diversity in large-scale LC-MS experiments.

Variate Associated Domain Adaptation for Unsupervised Multivariate Time Series Anomaly Detection

Multivariate Time Series Anomaly Detection (MTS-AD) is crucial for the effective management and maintenance of devices in complex systems such as server clusters, spacecrafts and financial systems etc. However, upgrade or cross-platform deployment of these devices will introduce the issue of cross-domain distribution shift, which leads to the prototypical problem of Domain Adaptation for MTS-AD. Compared with general domain adaptation problems, MTS-AD domain adaptation presents two peculiar challenges: 1) The dimensions of data from the source domain and the target domain are usually different, so alignment without losing any information is necessary. 2) The association between different variates plays a vital role in the MTS-AD task, which is overlooked by traditional domain adaptation approaches. Aiming at addressing the above issues, we propose a V ariate A ssociated domai N a D aptation method combined with a Gr A ph Deviation Network (abbreviated as VANDA ) for MTS-AD, which includes two major contributions. First, we characterize the intra-domain variate associations of the source domain by a graph deviation network (GDN), which can share parameters across domains without dimension alignment. Second, we propose a sliding similarity to measure the inter-domain variate associations and perform joint training by minimizing the optimal transport distance between source and target data for transferring variate associations across domains. VANDA achieves domain adaptation by transferring both variate associations and GDN parameters from the source domain to the target domain. We construct two pairs of MTS-AD datasets from existing MTS-AD data and combine three domain adaptation strategies with six MTS-AD backbones as the benchmark methods for experimental evaluation and comparison. Extensive experiments demonstrate the effectiveness of our approach, which outperforms the benchmark methods, and significantly improves the AD performance of the target domain by effectively utilizing the source domain knowledge.

Comparison of colorimetric methods for the analysis of total polyphenols in green tea extracts.

Two colorimetric methods are used to determine the total polyphenol contents of tea, namely, "the Folin-Ciocalteu method" defined by the International Organization for Standardization (ISO) and the "iron tartrate method" specified in the Standard Tables of Food Composition in Japan. In this study, we compared the Folin-Ciocalteu and iron tartrate methods using green tea extracts. When comparing the two methods, the sum of the four major catechins measured using high-performance liquid chromatography (HPLC) was regarded as the standard value. The total polyphenol contents obtained using the Folin-Ciocalteu method were closer to the HPLC value than those obtained using iron tartrate method. However, iron tartrate method is adequate if the current official method is improved, that is, our results suggest that the coefficients appropriate for common green tea varieties, as well as the degree and duration of cover cultivation, in the official iron tartrate method must be considered.

Evaluation of the combined toxicity of heavy metals and chlorpyrifos: A comparison of electrochemical and MTT methods

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Comparison of Feature Selection Methods—Modelling COPD Outcomes

Selecting features associated with patient-centered outcomes is of major relevance yet the importance given depends on the method. We aimed to compare stepwise selection, least absolute shrinkage and selection operator, random forest, Boruta, extreme gradient boosting and generalized maximum entropy estimation and suggest an aggregated evaluation. We also aimed to describe outcomes in people with chronic obstructive pulmonary disease (COPD). Data from 42 patients were collected at baseline and at 5 months. Acute exacerbations were the aggregated most important feature in predicting the difference in the handgrip muscle strength (dHMS) and the COVID-19 lockdown group had an increased dHMS of 3.08 kg (CI95 ≈ [0.04, 6.11]). Pack-years achieved the highest importance in predicting the difference in the one-minute sit-to-stand test and no clinical change during lockdown was detected. Charlson comorbidity index was the most important feature in predicting the difference in the COPD assessment test (dCAT) and participants with severe values are expected to have a decreased dCAT of 6.51 points (CI95 ≈ [2.52, 10.50]). Feature selection methods yield inconsistent results, particularly extreme gradient boosting and random forest with the remaining. Models with features ordered by median importance had a meaningful clinical interpretation. Lockdown seem to have had a negative impact in the upper-limb muscle strength.

Comparison of supine-prone percutaneous nephrolithotomy methods in the treatment of kidney stones in pediatric patients: prospective randomized study.

Mini-PCNL is one of the most effective surgical methods in the treatment of kidney stones in pediatric patients. In this study, we aimed to compare PCNL in the supine-prone position in pediatric patients (especially operation time, postop complications, hospital stay and stone-free rates).We conducted our study in a randomized and prospective manner. Patients with lower pole stones larger than 1cm, stones larger than 1.5cm in the pelvis, upper pole, midpole or multiple locations, and patients who did not respond to ESWL or whose family that preferred mini-PCNL to be the primary treatment were included in the study. Patients with any previous kidney stone surgery, patients with coagulation disorders and patients with retrorenal colon were excluded from the study. Between 2021 and 2023, a total of 144 patients underwent PCNL. 68 of these patients had supine PCNL and 76 prone PCNL. Postoperative Clavien grade1 complication occurred in a total of 7 patients in the prone position; Clavien grade1 complication occurred in 1 patient in the supine position. The mean operation time for prone PCNL was 119.88 ± 28.32min, and the mean operative time for supine PCNL was 98.12 ± 14.97 the mean hospitalization time in prone PCNL was 3.56 ± 1.12days, and 3.00 ± 0.85days in supine PCNL. In conclusion, supine PCNL is a safe and effective method in the treatment of pediatric kidney stones and postoperative complications were observed to be less; the operation time and hospital stay were shorter in supine PCNL.

A systematic comparison of deep learning methods for Gleason grading and scoring

A systematic comparison of deep learning methods for Gleason grading and scoring

Comparisons of noncoronary sinus pivot implantation (NCPI) and conventional method for transcatheter aortic valve replacement with self-expanding valve in pure aortic regurgitation (PAR).

As compared to treatment of aortic stenosis (AS), transcatheter aortic valve replacement (TAVR) using the commercially available valves to treat pure aortic regurgitation (PAR) has a lower device success rate and higher complication rates. The study compared the acute results between TAVR using a novel noncoronary sinus pivot implantation (NCPI) method and that using the conventional method, aiming to explore a more optimized and effective operation method for TAVR in PAR. PAR patients who underwent TAVR with self-expanding valves in our center from September 2021 to September 2023 were enrolledwere divided into the NCPI (group A, N = 16) and conventional method (group B, N = 39) groups. We analyzed the pre-operative evaluation parametersand procedural and postoperative dataof the two subgroups. The total patients' mean age was 71.2 ± 8.7 years and most were male (61.8%), with a mean Society of Thoracic Surgeons score of 3.4 ± 1.9%. The device success rate of groups A and B was 100% and 71.8%, respectively. In group B, 48.7% had major adverse cardiac events (MACE); 46.2% patients had permanent pacemaker implantation or valve in valve implantation. None had MACE in group A. The noncoronary sinus implantation depth in NCPI was -1.7 + 1.0and 5.2 + 6.7 mm in groups A and B (p < 0.001), respectively. TAVR with a self-expanding valve using the NCPI method had a higher procedure success rate and dramatically low complications than that using the conventional method in PAR patients.

Comparison of AC Loss Reduction Methods Based on Striation of Ag-Stabilized REBCO Tapes

Comparison of AC Loss Reduction Methods Based on Striation of Ag-Stabilized REBCO Tapes

Comparison of classical method and microdebrider technique for adenoidectomy in pediatric patients with obstructive sleep apnea.

The aim of this study was to evaluate the safety and efficacy of microdebrider adenoidectomy on sleep-disordered breathing among pediatric patients with OSA. In the microdebrider group (Group I), there were 30 Japanese OSA patients consisting of 26 boys and 4 girls. For comparison, we had 15 children (13 boys and 2 girls) who underwent classical adenoidectomy (Group II). Patients in Group I were selected from a pool of 95 pediatric Japanese OSA patients and were matched by age, preoperative AHI, and Kaup index with those in Group II.Parameters such as the amount of residual adenoid tissue, bleeding, duration of the procedure, and sleep-related metrics were compared between the two groups. A significant improvement in postoperative AHI was observed in Group I (p<0.05). The prevalence of AHI <1 was significantly higher in Group I compared with Group II (p<0.05). Additionally, the amount of postoperative residual adenoid was significantly less in Group I (3/30 of Grade 3 and 4 adenoid size) than in Group II (7/15, p<0.05). Furthermore, a reduction in postoperative AHI was proportionally associated with a decrease in residual adenoid. The newly developed microdebrider adenoidectomy technique for pediatric OSA patients with adenotonsillar hypertrophy demonstrated greater accuracy and efficacy in ameliorating sleep apnea symptoms compared with the standard adenoidectomy approach.

Comparison of methods to aggregate climate data to predict crop yield: an application to soybean

High-dimensional climate data collected on a daily, monthly, or seasonal time step are now commonly used to predict crop yields worldwide with standard statistical models or machine learning models. Since the use of all available individual climate variables generally leads to calculation problems, over-fitting, and over-parameterization, it is necessary to aggregate the climate data used as predictors. However, there is no consensus on the best way to perform this task, and little is known about the impacts of the type of aggregation method used and of the temporal resolution of weather data on model performances. Based on historical data from 1981 to 2016 of soybean yield and climate on 3447 sites worldwide, this study compares different temporal resolutions (daily, monthly, or seasonal) and dimension reduction techniques (principal component analysis (PCA), partial least square regression, and their functional counterparts) to aggregate climate data used as inputs of machine learning and linear regression (LR) models predicting yields. Results showed that random forest models outperformed and were less sensitive to climate aggregation methods than LRs when predicting soybean yields. With our models, the use of daily climate data did not improve predictive performance compared to monthly data. Models based on PCA or averages of monthly data showed better predictive performance compared to those relying on more sophisticated dimension reduction techniques. By highlighting the high sensitivity of projected impact of climate on crop yields to the temporal resolution and aggregation of climate input data, this study reveals that model performances can be improved by choosing the most appropriate time resolution and aggregation techniques. Practical recommendations are formulated in this article based on our results.

Novel Tools for Single Comparative and Unified Evaluation of Qualitative and Quantitative Bioassays: SS/PV–ROC and SS-J/PV-PSI Index–ROC Curves with Integrated Concentration Distributions, and SS-J/PV-PSI Index Cut-Off Diagrams

Background: This investigation is both a study of potential non-invasive diagnostic approaches for the bladder cancer biomarker UBC® Rapid test and a study including novel comparative methods for bioassay evaluation and comparison that uses bladder cancer as a useful example. The objective of the paper is not to investigate specific data. It is used only for demonstration, partially to compare ROC methodologies and also to show how both sensitivity/specificity and predictive values can be used in clinical diagnostics and decision making. This study includes ROC curves with integrated cut-off distribution curves for a comparison of sensitivity/specificity (SS) and positive/negative predictive values (PPV/NPV or PV), as well as SS-J index/PV-PSI index–ROC curves and SS-J/PV-PSI index cut-off diagrams (J = Youden, PSI = Predictive Summary Index) for the unified direct comparison of SS-J/PV results achieved via quantitative and/or qualitative bioassays and an identification of optimal separate or unified index cut-off points. Patients and Methods: According to the routine diagnostics, there were 91 patients with confirmed bladder cancer and 1152 patients with no evidence of bladder cancer, leading to a prevalence value of 0.073. This study performed a quantitative investigation of used-up test cassettes from the visual UBC® Rapid qualitative point-of-care assay, which had already been applied in routine diagnostics. Using a photometric reader, quantitative data could also be obtained from the test line of the used cassettes. Interrelations between SS and PV values were evaluated using cumulative distribution analysis (CAD), SS/PV–ROC curves, SS-J/PV-PSI index–ROC curves, and the SS-J/PV-PSI index cut-off diagram. The maximum unified SS-J/PV-PSI index value and its corresponding cut-off value were determined and calculated with the SS-J/PV-PSI index cut-off diagram. Results: The use of SS/PV–ROC curves with integrated cut-off concentration distribution curves provides improved diagnostic information compared to “traditional” ROC curves. The threshold distributions integrated as curves into SS/PV–ROC curves and SS-J/PV-PSI index–ROC curves run in opposite directions. In contrast to the SS–ROC curves, the PV–ROC and the novel PV-PSI index–ROC curves had neither an area under the curve (AUC) nor a range from 0% to 100%. The cut-off level of the qualitative assay was 7.5 µg/L, with a sensitivity of 65.9% and a specificity of 63.3%, and the PPV was 12.4% and the NPV was 95.9%, at a threshold value of 12.5 µg/L. Based on these set concentrations, the reader-based evaluation revealed a graphically estimated 5% increase in sensitivity and a 13% increase in specificity, as compared to the visual qualitative POC test. In the case of predictive values, there was a gain of 8% for PPV and 10% for NPV. The index values and cut-offs were as follows: visual SS-J index, 0.328 and 35 µg/L; visual PV-PSI index, 0.083 and 5.4 µg/L; maximal reader Youden index, 0.0558 and 250 µg/L; and maximal PV-PSI index, 0.459 and 250 µg/L, respectively. The maximum unified SS-J/PV-PSI index value was 0.32, and the cut-off was 43 µg/L. The reciprocal SS-J index correctly detected one out of three patients, while the reciprocal PV-PSI index gave one out of twelve patients a correct diagnosis. Conclusions: ROC curves including cut-off distribution curves supplement the information lost in “traditionally plotted” ROC curves. The novel sets of ROC and index–ROC curves and the new SS/PV index cut-off diagrams enable the simultaneous comparison of sensitivity/specificity and predictive value profiles of diagnostic tools and the identification of optimal cut-off values at maximal index values, even in a unifying SS/PV approach. Because the curves within an SS-J/PV-PSI index cut-off diagram are distributed over the complete cut-off range of a quantitative assay, this field is open for special clinical considerations, with the need to vary the mentioned clinical diagnostic parameters. Complete or partial areas over the x-axis (AOX) can be calculated for summarized quantitative or qualitative effectivity evaluations with respect to single and/or unified SS-J and PV-PSI indices and with respect to single, several, or several unified assays. The SS-J/PV-PSI index-AOX approach is a new tool providing additional joint clinical information, and the reciprocal SS-J indices can predict the number of patients with a correct diagnosis and the number of persons who need to be examined in order to correctly predict a diagnosis of the disease. These methods could be used in applications like medical or plant epidemiology, machine learning algorithms, and neural networks.

Comparison of assay methods for quantifying sex hormone concentrations across the menstrual cycle in rhesus macaques.

Immunoassays have been the preferred method for steroid hormone analysis for more than 50years. Automated immunoassays (AIAs) offer high-throughput, rapid data turnaround, and low cost for measuring steroid hormone concentrations. The application of liquid chromatography-tandem mass spectrometry (LC-MS/MS) for steroid quantification provides greater specificity and selectivity for individual steroids, the ability to simultaneously analyze multiple steroids, and high-throughput and automation. We compared AIA and LC-MS/MS for analysis of 17β-estradiol (E2) and progesterone (P4) over the course of several menstrual cycles in 12 rhesus macaques (Macaca mulatta). Serum samples were collected every four days across four menstrual cycles from each monkey. AIAs were performed on a Roche cobas e411 analyzer. Analysis of E2 and P4 was performed by LC-MS/MS on a Shimadzu-Nexera-LCMS-8060 instrument. Scatter plots with Passing-Bablok regression showed excellent agreement between AIA and LC-MS/MS for both E2 and P4. Bland-Altman plots revealed no bias for either method; however, AIA overestimated E2 at concentrations >140pg/ml and underestimated P4 at concentrations >4ng/ml compared to LC-MS/MS. A comparison of testosterone (T) concentrations measured by AIA and LC-MS/MS in the same samples was also performed. In contrast to E2 and P4, AIA and LC-MS/MS yielded significantly different results for T concentrations, with AIA consistently underestimating concentrations relative to those obtained by LC-MS/MS. Well-characterized AIAs are an excellent tool for daily monitoring of monkey menstrual cycles or providing single data points requiring fast turnaround. In certain situations where AIA may provide inaccurate estimations of E2 and P4 concentrations, LC-MS/MS assays are preferable.

PERBANDINGAN METODE DEMONSTRASI DAN METODE DISKUSI DALAM MENINGKATKAN PEMAHAMAN KONSEP TRIGONOMETRI PADA SISWA KELAS X SMASWASTA KAMPUS TELUK DALAM

The purpose of this research is to determine the comparison of demonstration methods and discussion methods in increasing understanding of trigonometry concepts in Class X SMA Swasta Teluk Dalam. This research uses a type of quantitative research, namely experimental class 1 using the demonstration method and experimental class 2 using the discussion method. The population in experimental class 1 is class X-A of the SMA Swasta Teluk Dalam, totaling 30 students, while the population in experimental class 2 is class X-B of the SMA Swasta Teluk Dalam the totaling 28 students. Results of the research stated that in experimental class 1 by carrying out the pretest the average learning outcome was 58,28 and the posttest obtained an average learning outcome of 73,41. Meanwhile, in experimental class 2, the pretest obtained an average learning result of 57,85 and the posttest obtained an average learning result of 61,32. So, there is a comparison of the demonstration method with the discussion method. The conclusion of the research based on hypothesis test calculations is that tcount = 2.74 is greater than ttable = 2.004 with a significance of 5% because tcount &gt; ttable then Ha is accepted and H0 is rejected, which means the research shows that there is a difference in understanding the concept of trigonometry between students taught using the demonstration method and students who are taught using the discussion method in class X of the SMA Swasta Teluk Dalam. Students taught using the demonstration method tend to have better understanding than students taught using the discussion method. It is hoped that every subject teacher applies the demonstration method to improve students' learning abilities and students' understanding of concepts in Trigonometry material as well as to serve as a guide or reference for every reader or researcher who wants to write their next thesis.

Comparison of serological and molecular methods for differentiation between genotype A and genotype B strains of small ruminant lentiviruses

Abstract Introduction Small ruminant lentiviruses (SRLV) cause multisystemic, degenerative and chronic disease in sheep and goats. There are five genotypes (A, B, C, D and E), of which A and B are the most widespread. The purpose of this study was to evaluate the serotyping efficiency of the Eradikit SRLV Genotyping ELISA and the molecular typing efficiency of a newly developed nested real-time PCR targeting the long terminal repeat–gag (LTR-gag) region using samples from animals infected with subtypes of SRLV known to circulate in Poland. Material and Methods A total of 97 sera samples taken from 34 sheep and 63 goats were immunoassayed, and 86 DNA samples from 31 sheep and 55 goats were tested with the PCR. All ruminants were infected with known SRLV strains of the A1, A5, A12, A13, A16, A17, A18, A23, A24, A27, B1 and B2 subtypes. Results A total of 69 (80.2%, 95% confidence interval 71.6%–88.8%) out of 86 tested samples gave positive results in the PCR. In 17 out of the 86 (19.8%) samples, no proviral DNA of SRLV was detected. The differentiation between MVV (genotype A) and CAEV (genotype B) by PCR matched the predating phylogenetic analysis invariably. No cross-reactivity was observed. On the other hand, the proportion of samples genotyped the same by the older phylogenetic analysis and the Eradikit SRLV Genotyping ELISA was 42.3%. The test was unable to classify 40.2% of samples, and 17.5% of sera were incorrectly classified. Conclusion Our results showed that the Eradikit SRLV genotyping kit is not a reliable method for predicting SRLV genotype, while the nested real-time PCR based on the LTR-gag region did prove to be, at least for genotypes A and B.

Analysis of Cellular Stress Assay Parameters and Intracellular ATP in Platelets: Comparison of Platelet Preparation Methods

Platelets are metabolically active, anucleated and small circulating cells mainly responsible for the prevention of bleeding and maintenance of hemostasis. Previous studies showed that platelets mitochondrial content, function, and energy supply change during several diseases such as HIV/AIDS, COVID-19, pulmonary arterial hypertension, and in preeclampsia during pregnancy. These changes in platelets contributed to the severity of diseases and mortality. In our previous studies, we have shown that the seahorse-based cellular stress assay (CSA) parameters are crucial to the understanding of the mitochondrial performance in peripheral blood mononuclear cells (PBMCS). Moreover, the results of CSA parameters were significantly influenced by the PBMC preparation methods. In this study, we assessed the correlation of CSA parameters and intracellular ATP content in platelets and evaluated the effects of platelet preparation methods on the results of CSA parameters and intracellular ATP content. We compared the results of CSA parameters and intracellular ATP content in platelets isolated by density centrifugation with Optiprep and simple centrifugation of blood samples without Optiprep. Platelets isolated by centrifugation with Optiprep showed a higher spare capacity, basal respiration, and maximal respiration than those isolated without Optiprep. There was a clear correlation between basal respiration and maximal respiration, and the whole-ATP content in both isolation methods. Moreover, a positive correlation was observed between the relative spare capacity and whole-cell ATP content. In conclusion, the results of seahorse-based CSA parameters and intracellular ATP content in platelets are markedly influenced by the platelet isolation methods employed. The results of basal respiration and maximal respiration are hallmarks of cellular activity in platelets, and whole-cell ATP content is a potential hint for basic platelet viability. We recommend further studies to evaluate the role of CSA parameters and intracellular ATP content in platelets as biomarkers for the diagnosis and prediction of disease states.

Compare Some Shrinkage Bayesian Estimation Method forGumbel-Max Distribution with Simulation

     The Gumbel max distribution is one of the most important statistical distributions because it has many applications, especially in the field of water research and the prediction of earthquakes and volcanoes. This work includes a comparison of several Shrinkage Bayesian methods, namely the Shrinkage Bayesian Square Loss Function, Shrinkage Bayesian Lenix Function, and Shrinkage Bayesian Unix Function to estimate the distribution parameter. The research also includes several simulated experiments according to the sample size change and the real value of the distribution parameter. The number of experiments is 15 simulated experiments based on the difference sample size and true distribution parameter values. The results of the simulation experiments are compared depending on each of the absolute least difference criteria (  and the mean squared error (). The comparison results show that the estimation method is affected by the sample size, and the real value of the distribution parameter. The best estimation method is the Shrinkage Bayesian Lenix Function. The Bayesian methods can be applied to other statistical distributions such that the Lindley Weibull distribution and logistics distribution.

Dietary analysis of wolf (Canis lupus) – a comparison of markers and methods

AbstractMetabarcoding is emerging as an alternative to morphological methods in noninvasive carnivore diet analysis based on scats. A number of metabarcoding markers have been developed but their comparative performance to recover DNA from scats remains mostly untested. We tested three markers covering a wide taxonomic range of prey items and compared them with the results of a morphological analysis. Morphological and genetic methods performed comparably regarding the identity of detected prey species, but the number of identified species varied strongly between markers. Only one, 12S-V5, amplified successfully in all samples and proved to be robust and reliable when working with the highly degraded DNA obtained from scats.