Calculated Coefficient Of Variation Research Articles

The 3D- Telomere Profiling Assay Identifies High Risk Smoldering Multiple Myeloma Patients with High Precision

Smoldering multiple myeloma (SMM) is an asymptomatic precursor stage of multiple myeloma (MM). According to the international Myeloma Working Group data (Blood Cancer J. 2020 Oct 16;10(10):102) the probability of progression to MM is 22% at 2 years, and 42% and 64% at 5 and 10 years, respectively. Thus, identification of patients with high risk of early progression to MM is crucial for optimal treatment management. Genomic instability is a sensitive indicator of disease progression in cancer. Telomere dysfunction is an early event in genomic instability. The 3-dimensional (3D) spatial profiling of telomeres using TeloView technology allows for quantification of telomere dysfunction and was shown to be instrumental in risk stratification of cancer patients generally, but particularly in selected hematological malignancies. Importantly, the utility of the 3D-telomere profiling was recently demonstrated in 2 clinical studies validating the utility of 3D telomere profiling as a structural biomarker to identify high risk SMM patients. The two studies achieved accuracy of >80% and specificity and sensitivity of over 80% & 76% respectively in a training dataset study followed by a blind validation (Kumar S.et al 2023. J Clin Oncol). To present the 3D telomere profiling assay as a reliable prognostic tool in the clinic, capable to precisely identify high risk SMM patients, it is important to demonstrate the repeatability and accuracy of the assay. In this study, we conducted a retrospective analytical validation including samples of 20 SMM patients with known progression outcome. The samples of each patient were blindly processed in triplets using the 3D-telomere assay, followed by the TeloView analysis. To eliminate any validation-bias the validation was conducted with uncontrolled variables. Samples were processed blindly by different operators on different dates using different instrumentation. We interrogated the repeatability and precision of the results of each patient analyzed on 2 levels. First, we calculated coefficient of variation (CV) of telomere predictors of each patient across the three runs; and secondly, we interrogated the repeatability of patient outcome using the scoring model developed and validated in (Kumar et al. 2023, J Clin Oncol) across the three runs of each patient. We set the acceptable concordance to 80% for CVs (CV <20%) and the acceptable repeatability of patient-outcome as predicted by the scoring model to 80% of the patients included in the study. We report CVs across all the telomere predictors, across the 3 runs of all patients ranging between 2.3 - 17.8. Furthermore, patient outcome as high/low risk of progression was consistent in 17 out of the 20 patients in all 3 runs (85%). The results of this study demonstrate the 3D-telomere profiling as an accurate and prognostic structural biomarker. The assay shows high level of precision, repeatability, and reliability, and presents a viable solution to accurately identify high risk SMM patients. This will potentially allow the treating physicians to make confident treatment decisions for high risk SMM patients based on the results of the 3D Telomere profiling assay.

Designing plots for precise estimation of forest attributes in landscapes and forests of varying heterogeneity

Models of relationships among forest inventory sampling efficiency and cluster plot configuration variables inform decisions by inventory planners. However, relationships vary under different spatial heterogeneity scenarios. To improve understanding of how spatial patterns of forests affect these relationships, we implemented a factorial experiment by simulating forest pattern at both the landscape and stand scales. We sampled these simulated forests with a variety of cluster plot configurations, calculated coefficient of variation (CV) of trees per hectare for each replicate, and tested the relationships among CV and the heterogeneity and cluster plot configuration factors within a linear mixed model framework. Both landscape- and stand-scale pattern aggregation had a significant relationship with CV. Changing cluster plot configuration factors did little to change the overall CV when using larger subplots but had some important effects when using smaller subplots. These impacts were stronger in the more uniform landscapes. Results were opposite for stand-scale heterogeneity; changing plot configuration in areas with aggregated patterns had a stronger impact than it did in areas with more uniform patterns. Results of this study reveal the importance of accounting for spatial pattern at multiple scales when making cluster configuration choices if the goal is statistical efficiency.

Development of monoclonal antibody‐based sandwich ELISA for detecting major mango allergen Man i1 in processed foods

AbstractMango (Mangifera indica L.) is a popular tropical fruit but also an allergenic source. In Taiwan, the packaging of any food product that contains mango must display an allergen warning. Therefore, establishing a reliable method for detecting mango residues in food products is important. In this study, a sandwich enzyme‐linked immunosorbent assay (sELISA) was developed to detect the major mango allergen Man i1. First, five batches of polyclonal and monoclonal antibodies against Man i1 were generated and used to identify the optimal antibody pair for sELISA. Using 2G5 mAb as the capture antibody and anti‐rMan i1 pAb as the detection antibody yielded the strongest assay signal. The limit of detection (LOD) and limit of quantification (LOQ) of the developed ELISA are estimated to be 3.9 and 21.2 ng/ml rMan i1, respectively, after optimization. The assay exhibits good specificity to mango and offers good precision and reproducibility since the calculated coefficient of variation (CV) of the intra‐ and inter‐assays were 5.5–11.7% and 7.4–12.4%, respectively. Finally, 23 commercial food products were evaluated using the developed sELISA and the results of this assay closely agreed (95.7%) with those of the Western blot. Thus, the developed sELISA provides a potential method for detecting mango allergens in foods for protecting people with mango allergy from the accidental ingestion of mango.

Estimating animal abundance and effort–precision relationship with camera trap distance sampling

AbstractEffective monitoring methods are needed for assessing the state of biodiversity and detecting population trends. The popularity of camera trapping in wildlife surveys continues to increase as they are able to detect species in remote and difficult‐to‐access areas. As a result, several statistical estimators of the abundance of unmarked animal populations have been developed, but none have been widely tested. Even where the potential for accurate estimation has been demonstrated, whether these methods estimators can yield estimates of sufficient precision to detect trends and inform conservation action remains questionable. Here, we assess the effort–precision relationship of camera trap distance sampling (CTDS) in order to help researchers design efficient surveys. A total of 200 cameras were deployed for 10 months across 200 km2 in the Taï National Park, Côte d'Ivoire. We estimated abundance of Maxwell's duikers, western chimpanzees, leopards, and forest elephants that are challenging to enumerate due to rarity or semi‐arboreality. To test the effects of spatial and temporal survey effort on the precision of CTDS estimates, we calculated coefficient of variation (CV) of the encounter rate from subsets of our complete data sets. Estimated abundance of leopard and Maxwell's duiker density (20% < CV < 30% and CV = 11%, respectively) were similar to prior estimates from the same area. Abundances of chimpanzees (20% < CV < 30%) were underestimated, but the quality of inference was similar to that reported after labor‐intensive line transect surveys to nests. Estimates for the rare forest elephants were potentially unreliable since they were too imprecise (60% < CV < 200%). Generalized linear models coefficients indicated that for relatively common, ground‐dwelling species, CVs between 10% and 20% are achievable from a variety of survey designs, including long‐term (6+ months) surveys at few locations (50), or short term (2‐week to 2‐month) surveys at 100–150 locations. We conclude that CTDS can efficiently provide estimates of abundance of multiple species of sufficient quality and precision to inform conservation decisions. However, estimates for the rarest species will be imprecise even from ambitious surveys and may be biased for species that exhibit strong reactions to cameras.

Impact of climatic variability on Aman rice production using fuzzy logic

Modern world is blessed by technical development. Developing agricultural sector has become a great demand nowadays, because people are increasing and the land is decreasing. Various methods are applying to improve the production in the agricultural sector. Among foods, rice is one of the major foods consumed by different types of people all over the world. So, in this research, fuzzy logic is used to analyse the Aman rice production. We considered the main factors related to Aman rice (BR23 Aman) productions are temperature, rainfall and area. We analysed the production estimation using collected data and an estimation is presented by using the fuzzy-based simulated result. We have calculated coefficient of variation (CV) for the three factors, and the result indicates that, the CV for temperature is 49.12% whereas CV value for rainfall and area is 29.68% and 22.79% respectively, which indicates BR23 Aman as temperature-sensitive.

Impact of climatic variability on Aman rice production using fuzzy logic

Modern world is blessed by technical development. Developing agricultural sector has become a great demand nowadays, because people are increasing and the land is decreasing. Various methods are applying to improve the production in the agricultural sector. Among foods, rice is one of the major foods consumed by different types of people all over the world. So, in this research, fuzzy logic is used to analyse the Aman rice production. We considered the main factors related to Aman rice (BR23 Aman) productions are temperature, rainfall and area. We analysed the production estimation using collected data and an estimation is presented by using the fuzzy-based simulated result. We have calculated coefficient of variation (CV) for the three factors, and the result indicates that, the CV for temperature is 49.12% whereas CV value for rainfall and area is 29.68% and 22.79% respectively, which indicates BR23 Aman as temperature-sensitive.

Real-Time PCR-based detection of bovine DNA by specific targeting on cytochrome-B

The design of specific primers is an interesting research topic such that it offers selective, specific, and effective DNA analysis using real-time PCR. This research was intended to detect bovine DNA using real-time PCR and specific primers to ensure the halal authenticity of food products . Primers of bovine DNA sequences were designed in the NCBI and Primer-BLAST programs. The outcome validation was assessed using several parameters, namely specificity, repeatability, and linearity by real-time PCR. Primer specificity test was performed on fresh tissue (pork and negative control), while the repeatability test used six replications and was based on the calculated coefficient of variation (CV). In the linearity test, six different DNA concentrations (50000, 10000, 5000, 500, 100, and 50 pg/µL) were examined to obtain the efficiency value. Using the specific primer from Cytochrome-B, the real-time PCR could specifically identify the presence of bovine DNA at the optimum annealing temperature of 58.7 0 C. The  repeatability  analysis yielded a coefficient of variation (CV) of 0.57 %, while the linearity test produced an efficiency  value of  206 %. These figures confirm that the method employed  in this study is not only specific but also sensitive and reliable for detecting bovine DNA. Real-time PCR using specific primer targeting on the cytochrome-B region of bovine DNA (forward: CTACTGACACTCACATGAATTGG; reverse CACTAGGATGAGGAGAAAGTATAGG) can be used to identify bovine DNA and distinguish it from porcine DNA.

Statistical Comparative Study of the Trend and Variation of Meteorological Parameters in Abeokuta, South-West Nigeria

This study focuses on the statistical comparative study of the trend and variation of meteorological parameters covering a 10 year period (2001-2010) in the capital and largest city of Ogun State, Abeokuta, southwest region of Nigeria. The analyzed meteorological parameters were: wind speed, vapour pressure, relative humidity, temperature, sunshine and rainfall covering 10 years. The calculated coefficient of variation (CV) for sunshine (22.78%), wind speed (21.55%), and rainfall (99.12%) is a proof of exceedance of variability of threshold of 10% while the CV calculated for air temperature (5.74%), relative humidity (4.52%) and vapour pressure (5.22%) show no significant variability. Significance test of meteorological parameters’ trend reveals a notable reduction in the values of vapour pressure, air temperature and relative humidity. It is, however, difficult to argue for a well-defined change in most of the meteorological parameters based on the monthly time series analyses performed in this work. Only wind speed shows a statistically significant increasing trend during the period of observation at 1% significance level. The trend revealed by rainfall and sunshine is statistically not significant. ANOVA test of significant difference among meteorological parameters show a p-value (Sig.) of 0.000 is an indication of the significant difference in the analyzed mean monthly coefficient of variation for the meteorological parameters under study. The Tukey’s multiple pair comparisons test, however, show that there is a significant difference between the mean monthly CV of rainfall–sunshine, rainfall-vapour pressure, rainfall-wind speed, rainfall-air temperature and rainfall-relative humidity. At the significance level of 5%, the calculated mean monthly CV of rainfall is significantly different from the mean monthly CV of other climatic parameters.

3A1-V02 トレッドミルを用いた脛骨疲労骨折発生リスクの評価(デジタルヒューマン)

Tibial stress fractures are one of the most common and potentially serious overuse injuries in runners. Despite the fact that the tibial stress fractures are related to vertical ground reaction force at early contact phase, a few study has been done for quantification of the variability of the risk parameters. The aim of this study was to quantify the variability of risk parameters for the stress fractures in able-bodied runners. Eight male subjects were asked to run at three different velocities (2.5, 3.0, 3.5 m/s) on a treadmill mounted on the force plates. From the vertical ground reaction force, we calculated coefficient of variation (CV) following lower extremity loading variables; vertical impact peak, vertical instantaneous loading rate and vertical average loading rate. We found that there were no significant differences in the CV of the loading variables in each speed, indicating that variability of loading variables during running is independent from running speeds.

Magnetic cobalt-zinc ferrite/PVAc nanocomposite: synthesis and characterization

Metal oxide nanoparticles are the subject of current interest because of their unusual optical, electronic, and magnetic properties. In this work, cobalt zinc ferrite (\( {\text{Co}}_{0.3} {\text{Zn}}_{0.7} {\text{Fe}}_{2} {\text{O}}_{4} \)) nanoparticles have been synthesized successfully through redox chemical reaction in aqueous solution. The synthesized \( {\text{Co}}_{0.3} {\text{Zn}}_{0.7} {\text{Fe}}_{2} {\text{O}}_{4} \) nanoparticles have been used for the preparation of homogenous polyvinyl acetate-based nanocomposite (\( {\text{Co}}_{0.3} {\text{Zn}}_{0.7} {\text{Fe}}_{2} {\text{O}}_{4} /{\text{PVAc}} \)) via in situ emulsion polymerization method. Structural, morphological and magnetic properties of the products were determined and characterized in detail by X-ray powder diffractometry (XRD), Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), transmission electron microscopy (TEM) and vibrating sample magnetometer (VSM). The XRD patterns of the \( {\text{Co}}_{0.3} {\text{Zn}}_{0.7} {\text{Fe}}_{2} {\text{O}}_{4} \) confirmed that the formed nanoparticles are single crystalline. According to TEM micrographs, the synthesized \( {\text{Co}}_{0.3} {\text{Zn}}_{0.7} {\text{Fe}}_{2} {\text{O}}_{4} \) nanoparticles had nano-needle morphology with an average particle size of 20 nm. The calculated coefficient of variation (CV) of nanoparticles diameters obtained by TEM micrographs was 16.77. The \( {\text{Co}}_{0.3} {\text{Zn}}_{0.7} {\text{Fe}}_{2} {\text{O}}_{4} \) nanoparticles were dispersed almost uniformly in the polymer matrix as was proved by SEM technique. The magnetic parameters of the samples, such as saturation magnetization (Ms) and coercivity (Hc) were measured, as well. Magnetization measurements indicated that the saturation magnetization of synthesized \( {\text{Co}}_{0.3} {\text{Zn}}_{0.7} {\text{Fe}}_{2} {\text{O}}_{4} /{\text{PVAc}} \) nanocomposites was markedly less than that of \( {\text{Co}}_{0.3} {\text{Zn}}_{0.7} {\text{Fe}}_{2} {\text{O}}_{4} \) magnetic nanoparticles. However, the nanocompoites exhibited super-paramagnetic behavior at room temperature under an applied magnetic field.