Average Coefficient Of Variation Research Articles

A Comprehensive and Repeatable Contrast-Enhanced Ultrasound Quantification Approach for Clinical Evaluations of Tumor Blood Flow.

The aim of this study is to define a comprehensive and repeatable contrast-enhanced ultrasound (CEUS) imaging protocol and analysis method to quantitatively assess lesional blood flow. Easily repeatable CEUS evaluations are essential for longitudinal treatment monitoring. The quantification method described here aims to provide a structure for future clinical studies. This retrospective analysis study included liver CEUS studies in 80 patients, 40 of which contained lesions (primarily hepatocellular carcinoma, n = 28). Each patient was given at least 2 injections of a microbubble contrast agent, and 60-second continuous loops were acquired for each injection to enable evaluation of repeatability. For each bolus injection, 1.2 mL of contrast was delivered, whereas continuous, stationary scanning was performed. Automated respiratory gating and motion compensation algorithms dealt with breathing motion. Similar in size regions of interest were drawn around the lesion and liver parenchyma, and time-intensity curves (TICs) with linearized image data were generated. Four bolus transit parameters, rise time (RT), mean transit time (MTT), peak intensity (PI), and area under the curve (AUC), were extracted either directly from the actual TIC data or from a lognormal distribution curve fitted to the TIC. Interinjection repeatability for each parameter was evaluated with coefficient of variation. A 95% confidence interval was calculated for all fitted lognormal distribution curve coefficient of determination (R2) values, which serves as a data quality metric. One-sample t tests were performed between values obtained from injection pairs and between the fitted lognormal distribution curve and direct extraction from the TIC calculation methods to establish there were no significant differences between injections and measurement precision, respectively. Average interinjection coefficient of variation with both the fitted curve and direct calculation of RT and MTT was less than 21%, whereas PI and AUC were less than 40% for lesion and parenchyma regions of interest. The 95% confidence interval for the R2 value of all fitted lognormal curves was [0.95, 0.96]. The 1-sample t test for interinjection value difference showed no significant differences, indicating there was no relationship between the order of the repeated bolus injections and the resulting parameters. The 1-sample t test between the values from the fitted lognormal distribution curve and the direct extraction from the TIC calculation found no statistically significant differences (α = 0.05) for all perfusion-related parameters except lesion and parenchyma PI and lesion MTT. The scanning protocol and analysis method outlined and validated in this study provide easily repeatable quantitative evaluations of lesional blood flow with bolus transit parameters in CEUS data that were not available before. With vital features such as probe stabilization ideally performed with an articulated arm and an automated respiratory gating algorithm, we were able to achieve interinjection repeatability of blood flow parameters that are comparable or surpass levels currently established for clinical 2D CEUS scans. Similar values and interinjection repeatability were achieved between calculations from a fitted curve or directly from the data. This demonstrated not only the strength of the protocol to generate TICs with minimal noise, but also suggests that curve fitting might be avoided for a more standardized approach. Utilizing the imaging protocol and analysis method defined in this study, we aim for this methodology to potentially assist clinicians to assess true perfusion changes for treatment monitoring with CEUS in longitudinal studies.

Design and Testing of Electric Drive System for Maize Precision Seeder

To improve the expandability, seeding accuracy, and operating speed range of the electric drive system (EDS) of precision seeders, this study constructed an EDS based on a controller area network (CAN) bus and designed a motor controller based on a field-orientated control (FOC) algorithm. Full-factorial bench and field tests based on seed spacing (0.1, 0.2, and 0.3 m) and operating speed (3, 6, 9, 12, and 15 km/h) were carried out to evaluate the performance of the EDS. The results of bench tests showed that seeding quality varied inversely with operating speed and positively with seed spacing. The average quality of feed index (QFI) at 0.1, 0.2, and 0.3 m seed spacing in bench tests was 88.38%, 96.67%, and 97.36%, with the average coefficient of variation (CV) being 20.13%, 16.27%, and 13.20%. Analysis of variance confirmed that both operating speed and seed spacing had a significant effect on QFI and CV (p < 0.001). The analysis of motor rotational speed accuracy showed that the relative error of motor rotational speed above 410 rpm did not exceed 2.24%, and the relative error had less influence on the seeding quality. The average QFI was 85.93%, 95.91%, and 96.24%, with the average CV being 21.12%, 15.50%, and 16.49% at 0.1, 0.2, and 0.3 m seed spacing in field tests. The methods and results of this study can provide a reference for the design and optimization of the EDS in a maize precision seeder and provide an effective solution for the improvement of maize yields.

Measurement of absolute abundance of crystallins in human and αA N101D transgenic mouse lenses using 15N-labeled crystallin standards

Stable isotope labeled standards of all major human lens crystallins were created to measure the abundance of lens endogenous crystallins from birth to adulthood. All major human crystallins (αA, αB, βA2, βA3/A1, βA4, βB1, βB2, βB3, γA, γB, γC, γD, γS) were cloned with N-terminal 6 x His tagged SUMO for ease of purification and the ability to generate natural N-termini by SUMO protease cleavage when producing crystallins for structure/function studies. They were then expressed in 15N-enriched media, quantified by mass spectrometry, and mixed in proportions found in young human lens to act as an artificial lens standard. The absolute quantification method was tested using soluble protein from 5-day, 23-day, 18-month, and 18-year-old human lenses spiked with the 15N artificial lens standard. Proteins were trypsinized, relative ratios of light and heavy labeled peptides determined using high-resolution precursor and data independent MS2 scans, and data analysis performed using Skyline software. Crystallin abundances were measured in both human donor lenses and in transgenic mouse αA N101D cataract lenses. Technical replicates of human crystallin abundance measurements were performed with average coefficients of variation of approximately 2% across all 13 crystallins. αA crystallin comprised 27% of the soluble protein of 5-day-old lens and decreased to 16% by 18-years of age. Over this time period αB increased from 6% to 9% and the αA/αB ratio decreased from 4.5/1 to 2/1. γS-crystallin also increased nearly 2-fold from 7% to 12%, becoming the 3rd most abundant protein in adult lens, while βB1 increased from 14% to 20%, becoming the most abundant crystallin of adult lens. Minor crystallins βA2, βB3, and γA comprised only about 1% each of the newborn lens soluble protein, and their abundance dropped precipitously by adulthood. While 9 of the SUMO tagged crystallins were useful for purification of crystallins for structural studies, γA, γB, γC, and γD were resistant to cleavage by SUMO protease. The abundance of WT and N101D human αA in transgenic mouse lenses was approximately 40-fold lower than endogenous mouse αA, but the deamidation mimic human αA N101D was less soluble than human WT αA. The high content of αA and the transient abundance of βA2, βB3, and γA in young lens suggest these crystallins play a role in early lens development and growth. βB1 becoming the most abundant crystallin may result from its role in promoting higher order β-crystallin oligomerization in mature lens. The full set of human crystallin expression vectors in the Addgene repository should be a useful resource for future crystallin studies. 15N labeling of these crystallins will be useful to accurately quantify crystallins in lens anatomic regions, as well as measure the composition of insoluble light scattering crystallin aggregates. The standards will also be useful to measure the abundance of crystallins expressed in transgenic animal models.

B-156 Extraction strategy for therapeutic drug monitoring of sirolimus and tacrolimus using volumetric absorptive microsampling

Abstract Background Following organ transplantation, patients are placed on immunosuppressant drugs (ISDs) to minimize the risk of rejection. Sirolimus and tacrolimus are two of the most widely used ISDs, however, due to their narrow therapeutic indices, patients require frequent therapeutic drug monitoring (TDM). Recurrent venipuncture can become uncomfortable and disruptive, especially in the pediatric population. Therefore, we describe an extraction method using dried whole blood from volumetric absorptive microsampling (VAMS) devices for the detection of sirolimus and tacrolimus by turbulent flow liquid chromatography tandem mass spectrometry (TFC-MS/MS). The use of VAMS in the clinical laboratory will provide ISD patients with a convenient alternative to traditional blood draws. Methods MassTrak immunosuppressant calibrators based on a whole blood matrix (Waters) were applied to 30 μL VAMS Mitra devices (Neoteryx) and dried overnight. To extract the whole blood off of VAMS tip, we tested various methanol:water solvent ratios, of which 30 μL was added to the device. Tips were extracted using ultrasonication (30 min), vortexing (5 min), and centrifugation. Once extracted from the tip, 25 mM zinc sulfate was added to whole blood extract at a 1:1 (v/v) ratio. An acetonitrile and methanol extraction reagent was then added to the whole blood/zinc sulfate solution at a 2:1 (v/v) ratio. After brief vortexing, samples were centrifuged at 16,060 × g (10 min) and tested using an established TFC-MS/MS method which deploys a TLX-2 system for sample preparation coupled to a Q-Trap tandem mass spectrometer (AB Sciex 5500). Results A 80:20 (v/v) water:methanol extraction solvent yielded the greatest extraction efficacy for both sirolimus and tacrolimus from the VAMS tips compared to other tested ratios. We established a 5-point calibration curve to correlate the measured values of ISDs with known MassTrak calibration standard concentrations. The resulting average calibration curve from 3 independent experiments was highly linear for both sirolimus (R2= 0.992; slope= 1.1; intercept= 0.94) and tacrolimus (R2= 0.996; slope= 1.1; intercept = 0.8819). Our VAMS whole blood extraction strategy was correlated to the established neat whole blood protocol, which utilized all of the sample preparation steps outlined above except the initial extraction from the VAMS tip. The average extraction efficacy was 89.1% for sirolimus with an average coefficient of variation (CV%) of 12.1% across 3 independent experiments. For tacrolimus, we demonstrated an average extraction efficacy of 100.1% with an average CV% of 8.4%, again across 3 independent experiments. Conclusions We demonstrate the feasibility of using a VAMS approach to TDM of sirolimus and tacrolimus. Our results demonstrate favorable recoveries for both of the tested drugs, evidenced by high recoveries of the external calibration standards. Additionally, our method exhibited high extraction efficacy and low variability. Further validation studies, including the utilization of clinical samples is necessary to confirm our preliminary findings.

Memory-type time-between-events charts using nonhomogeneous Poisson process

The traditional time-between-events (TBE) control charts are developed in non-adaptive fashion assuming the Poisson process, where the TBE follows the exponential distribution. However, in many situations we need an adaptive strategy, especially for healthcare or system monitoring. The focus of this study is to introduce new exponentially weighted moving average and cumulative sum adaptive TBE control charts for high-quality processes based on nonhomogeneous Poisson process by assuming the power law intensity. Charts assuming the nonhomogeneous Poisson process are dynamic and can be used where the underlying failure rate may be changing over time. The performance of the proposed control charts is evaluated using the average run length and coefficient of variation of the run length distribution. Three real data examples which correspond to different shape parameters of the power law process are also discussed in the article.

Identification of Priority Areas for Carbon Compensation in Chongqing Based on the Difference in Land Use Carbon Budget

This study aimed to explore the spatiotemporal patterns and balance characteristics of land use carbon budget, measure the value of carbon compensation, and delineate carbon compensation type zoning to provide scientific reference for further strengthening the connection between the construction of an ecological compensation system and the "dual carbon" target task. Based on the land cover data of Chongqing from 2000 to 2020, this study analyzed the spatiotemporal dynamics and balance relationship characteristics of the land use carbon budget. By using the revised carbon compensation model to measure the horizontal compensation standards, the normalized revealed comparative advantage （NRCA） index and K-means clustering analysis method were used to divide the carbon compensation area. The research results demonstrated that： ① the total land use carbon sequestration in Chongqing grew slowly from 2000 to 2020, whereas carbon emissions continued to increase significantly, and the net carbon emissions showed a distribution pattern of "high in the center and low in the two wings." ② The average coefficient of variation in Chongqing was 0.602, and the carbon emission economy contributive coefficient and carbon ecological support coefficient were concentrated between 0.64-1.14 and 0.00-32.86, respectively. The difference in the contribution of carbon emissions and economic benefits between districts and counties was relatively small, but there was a mismatch between carbon supply and demand. ③ A significant spatial difference existed in the value of carbon compensation, with a total of 1.098 billion yuan in carbon payment and 634 million yuan in carbon compensation, respectively. Moreover, it was ultimately determined that there were eight key payment areas, seven general payment areas, three key compensation areas, and 20 general compensation areas. In conclusion, the research results can provide a reference for implementing differentiated development strategies in different types of carbon compensation regions, improve the collaborative governance capacity of the regional ecological environment, and promote the achievement of carbon neutrality goals.

Comparing 3D imaging devices for the measurement of cutaneous neurofibromas in patients with Neurofibromatosis Type 1.

Cutaneous neurofibromas (cNFs) are a major cause of disfigurement in patients with Neurofibromatosis Type 1 (NF1). However, clinical trials investigating cNF treatments lack standardised outcome measures to objectively evaluate changes in cNF size and appearance. 3D imaging has been proposed as an objective standardised outcome measure however various systems exist with different features that affect useability in clinical settings. The aim of this study was to compare the accuracy, precision, feasibility, reliability and accessibility of three imaging systems. We compared the Vectra-H1, LifeViz-Micro and Cherry-Imaging systems. A total of 58 cNFs from 13 participants with NF1 were selected for imaging and analysis. The primary endpoint was accuracy as measured by comparison of measurements between imaging systems. Secondary endpoints included reliability between two operators, precision as measured with the average coefficient of variation, feasibility as determined by time to capture and analyse an image and accessibility as determined by cost. There was no significant difference in accuracy between the three devices for length or surface area measurements (p>0.05), and reliability and precision were similar. Volume measurements demonstrated the most variability compared to other measurements; LifeViz-Micro demonstrated the least measurement variability for surface area and image capture and analysis were fastest with LifeViz-Micro. LifeViz-Micro was better for imaging smaller number of cNFs (1-3), Vectra-H1 better for larger areas and Cherry for uneven surfaces. All systems demonstrated excellent reliability but possess distinct advantages and limitations. Surface area is the most consistent and reliable parameter for measuring cNF size in clinical trials.

Murmansk Marine Biological Institute of Kola Scientific Center of the Russian Academy of Sciences

The authors assess the wind potential indicators and the scale of its use for power supply of hard-to-reach off-grid settlements in the eastern Russian Arctic. The primary challenge facing autonomous power plants is fuel delivery due to long distances and underdeveloped transport infrastructure. The use of wind power plants will reduce fuel consumption and cut the cost of energy production. The researchers use ground-based measurement data and the characteristics of existing autonomous power plants as initial data when assessing the rational capacity of wind power plants. They employ authoring research methods. Via Wind-MCA program they estimate wind potential indicators: average wind speed, capacity factor, and coefficient of wind speed variation. The research results are presented in cartographic form. The rational capacities of wind power plants as part of hybrid energy systems are determined using the generalized dependencies method based on the maximum load of a populated area and calculated wind potential indicators, taking into account the characteristic intra-annual distribution of wind speeds. The best conditions for the development of wind energy are observed on the coast of the Arctic seas in the Krasnoyarsk Territory and the Chukot Autonomous Area. The rational capacity of wind power plants in zones of high wind potential in hard-to-reach areas of eastern Russian Arctic is estimated at 12,5 MW.

Multiplex reverse transcription recombinase polymerase amplification combined with lateral flow biosensor for simultaneous detection of three viral pathogens in cattle

Bovine viral diarrhea virus (BVDV), bovine epidemic fever virus (BEFV), and bovine respiratory syncytial virus (BRSV) cause respiratory symptoms in cattle. The absence of rapid, precise, and easily accessible diagnostic methods poses difficulties for herders and veterinary epidemiologists during outbreaks of major infectious animal diseases. Considering the mixed infection of viruses, a multiple-detection method, reverse transcription recombinase polymerase amplification (mRT-RPA) combined with a lateral flow biosensor (LFB), was established to simultaneously detect the three pathogens. This technique is based on the specific binding of three differently labeled RT-RPA products (DNA sequences) to antibodies on the three test lines of the LFB, achieving multiplex detection through the presence or absence of coloration on the LFB test lines. The fluorescence values of the LFB test lines are recorded by a test strip reader. The mRT-RPA-LFB assay completes detection at a constant temperature of 41 °C within 33 min. The limits of detection (LODs) for BVDV, BEFV and BRSV were 2.62 × 101, 2.42 × 101 and 2.56 × 101 copies/μL, respectively. No cross-reactivity was observed with the other six bovine viruses. The developed method showed satisfactory intra- and inter-assay precision, and the average coefficients of variation were ranged from 2.92 % to 3.99 %. The diagnostic sensitivity and specificity were 98.11 % and 100 %, respectively, which were highly consistent with the RT-qPCR assay, and the kappa value was 0.988 (95 % confidence interval, CI). In general, the mRT-RPA-LFB assay has the potential to become a powerful tool for rapid screening of cattle diseases because of its advantages such as fast detection speed, convenient operation, strong specificity, and high sensitivity.

Analysis of Phenotypic Trait Variation in Germplasm Resources of Lycium ruthenicum Murr.

Exploring the phenotypic trait variation and diversity of Lycium ruthenicum germplasm resources can support selection, breeding, and genetic improvement, enhancing agricultural production. This study collected 213 wild Lycium ruthenicum seedlings from a resource nursery in Alxa League, Inner Mongolia. These seedlings originated from eight sources across four provinces. Using 11 pseudo-qualitative traits and 20 quantitative traits, the phenotypic variation of the germplasm was analyzed. The analysis involved the coefficient of variation, Shannon–Wiener index (H), Simpson’s genetic diversity index (D), principal component analysis, correlation analysis, and Q-type cluster analysis. The results showed that the variation range of 31 phenotypic traits across the 213 Lycium ruthenicum germplasm resources was 17.26% to 105.41%, with an average coefficient of variation of 39.85%. The H and D indexes ranged from 0.18 to 1.58 and 0.20 to 0.75, respectively. For the 11 pseudo-qualitative traits, the H and D ranges were 0.18 to 1.58 and 0.07 to 0.74, with average values of 0.77 and 0.42. For the quantitative traits, the H and D ranges were 0.54 to 1.49 and 0.25 to 0.75, with average values of 1.21 and 0.63. This indicates that Lycium ruthenicum germplasm resources exhibit significant phenotypic diversity, with quantitative traits showing higher diversity than pseudo-qualitative traits. Principal component analysis revealed that the cumulative variance contribution rate of the first 10 principal components was 74.03%, comprehensively reflecting the information of the 31 traits. Q-type cluster analysis grouped the 213 Lycium ruthenicum germplasm resources into six clusters, each with distinct phenotypic characteristics. This analysis also identified the trait characteristics and breeding value of each cluster. The results of this study provide valuable information on the genetic improvement, conservation, and evaluation of Lycium ruthenicum germplasm resources.

Improving Radiometric Block Adjustment for UAV Multispectral Imagery under Variable Illumination Conditions

Unmanned aerial vehicles (UAVs) equipped with multispectral cameras offer great potential for applications in precision agriculture. A critical challenge that limits the deployment of this technology is the varying ambient illumination caused by cloud movement. Rapidly changing solar irradiance primarily affects the radiometric calibration process, resulting in reflectance distortion and heterogeneity in the final generated orthomosaic. In this study, we optimized the radiometric block adjustment (RBA) method, which corrects for changing illumination by comparing adjacent images and from incidental observations of reference panels to produce accurate and uniform reflectance orthomosaics regardless of variable illumination. The radiometric accuracy and uniformity of the generated orthomosaic could be enhanced by improving the weights of the information from the reference panels and by reducing the number of tie points between adjacent images. Furthermore, especially for crop monitoring, we proposed the RBA-Plant method, which extracts tie points solely from vegetation areas, to further improve the accuracy and homogeneity of the orthomosaic for the vegetation areas. To validate the effectiveness of the optimization techniques and the proposed RBA-Plant method, visual and quantitative assessments were conducted on a UAV-image dataset collected under fluctuating solar irradiance conditions. The results demonstrated that the optimized RBA and RBA-Plant methods outperformed the current empirical line method (ELM) and sensor-corrected approaches, showing significant improvements in both radiometric accuracy and homogeneity. Specifically, the average root mean square error (RMSE) decreased from 0.084 acquired by the ELM to 0.047, and the average coefficient of variation (CV) decreased from 24% (ELM) to 10.6%. Furthermore, the orthomosaic generated by the RBA-Plant method achieved the lowest RMSE and CV values, 0.039 and 6.8%, respectively, indicating the highest accuracy and best uniformity. In summary, although UAVs typically incorporate lighting sensors for illumination correction, this research offers different methods for improving uniformity and obtaining more accurate reflectance values from orthomosaics.

Development of a Sensitive Monoclonal Antibody-Based Colloidal Gold Immunochromatographic Strip for Lomefloxacin Detection in Meat Products.

Lomefloxacin (LOM), an antibiotic crucial for preventing various animal diseases in animal husbandry, can pose serious health risks when found in excessive amounts in meat products. The development of highly specific and sensitive colloidal gold immunochromatographic test strips is essential for the accurate detection of this class of antibiotics. Our study utilized a monoclonal antibody (mAb) assay and immunochromatographic strips to detect lomefloxacin residues in meat products. The results showed minimal cross-reactivity with other structural analogs, with a maximum half inhibitory concentration (IC50) of 0.93 ng/mL and a linear range of 0.38 to 2.3 ng/mL for the indirect competitive enzyme-linked immunosorbent assay (ic-ELISA). The recovery of LOM was 80% to 120%, with an average coefficient of variation below 5%. The immunochromatographic strip test results showed a visual detection limit of 2.5 ng/g, meeting the market requirements for the test. This study highlights the significance of specific and sensitive testing methods for detecting lomefloxacin, ensuring consumers' safety and health.

Optimization of Operational Parameters of Plant Protection UAV.

The operational parameters of plant protection unmanned aerial vehicles (UAVs) significantly impact spraying effectiveness, but the underlying mechanism remains unclear. This paper conducted a full factorial experiment with varying flight speeds, heights, and nozzle flow rates to collect parameter space data. Using the Kriging surrogate model, we characterized this parameter space and subsequently optimized the average deposition rate and coefficient of variation by employing a variable crossover (mutation) probability multi-objective genetic algorithm. In the obtained Pareto front, the average sedimentation rate is no less than 46%, with a maximum of 56.08%, and the CV coefficient is no more than 13.91%, with a minimum of only 8.42%. These optimized parameters enhance both the average deposition rate and spraying uniformity compared to experimental data. By employing these optimized parameters in practical applications, a balance between the maximum average deposition rate and minimum coefficient of variation can be achieved during UAV spraying, thereby reducing pesticide usage, promoting sustainable agriculture, and mitigating instances of missed spraying and re-spraying.

Spatiotemporal Variation Characteristics and Driving Factors of Vegetation NPP in the Ulansuhai Nur Basin from 2001 to 2020

Vegetation net primary productivity （NPP） represents the ability of plants to fix ecosystem carbon, which is a key indicator to determine the health status and sustainable development of ecosystems. Its spatial and temporal changes and driving factors play an important role in revealing the status of vegetation restoration and guiding ecological restoration. Based on MODIS17A3 NPP data, land use, and meteorological data from 2001 to 2020, the temporal and spatial variation characteristics and driving factors of vegetation NPP in the Ulansuhai Nur Basin of Inner Mongolia were explored by using the methods of coefficient of variation, Theil-Sen Median trend analysis, Mann-Kendall significance test, Hurst index, and Geodetector. The results showed that： ① From 2001 to 2020, the vegetation NPP in the Ulansuhai Nur Basin showed a fluctuating upward trend, with an average value （in terms of C） of 141.03 g·（m2·a）-1 and an average increase rate of 2.33 g·（m2·a）-1. The vegetation NPP had obvious spatial differentiation, which was characterized by high in the southwest and low in the northeast and high in Hetao Plain and low in sandy land and mountainous areas. ② NPP mainly showed an increasing trend, and the area proportions of increasing, decreasing, and unchanged areas were approximately 80%, 3%, and 17%, respectively. The average coefficient of variation of vegetation NPP was 0.149, which mainly showed low fluctuation change, and the area accounted for approximately 51%. The future change trend of NPP was mainly characterized by anti-persistence, with an area ratio of approximately 75%. ③ Land use, altitude, maximum temperature, and slope were the dominant driving factors of variation NPP change in the Ulansuhai Nur Basin, and the q values were all above 0.200. The interaction between altitude and relative humidity had the greatest explanatory power for the spatial differentiation of vegetation NPP in the Ulansuhai Nur Basin. There were significant differences in the explanatory power of land use and all factors except nighttime light to the spatial differentiation of vegetation NPP in the Ulansuhai Nur Basin. According to the research results, in the future, we should strengthen the ecosystem management of the Ulansuhai Nur Basin； continue to implement strict ecological protection and restoration policies； and comprehensively consider factors such as climate, topography, and human activities to carry out comprehensive ecological management according to local conditions to improve the quality of ecosystem services.

A multi reaction kinetic model to describe the enzymatic transesterification reaction of jatropha oil using a fermented solid containing lipases

The advancement of more precise tools for sustainable process design in enzymatic biodiesel synthesis from renewable sources is crucial. Kinetics of solvent-free transesterification reactions were conducted across a temperature spectrum from 30 °C to 60 °C, utilizing Jatropha curcas oil (TG) and ethanol as substrates, alongside a fermented solid by Rhizopus homothallicus as the biocatalyst. The dynamics of chemical species concentrations were monitored through High-performance Thin-Layer Chromatography. Maximum productivities were achieved at 35 °C and 60 °C for biodiesel (293.24 and 299.02 g kg biocat−1 h−1, respectively), at 40 °C for diglycerides (1018.36 g kg biocat−1 h−1), and at 35 °C for monoglycerides (560.75 g kg biocat−1 h−1). Maximum yields were determined at 30 °C for fatty acid ethyl esters (0.56 g gTG−1), and at 40 °C for diglycerides (0.53 g gTG−1) and monoglycerides (0.30 g gTG−1). Based on the experimental findings, a kinetic model was formulated encompassing three reversible transesterification reactions. Individual reactions were structured following classical biochemical kinetics, inclusive of ethanol inhibition. Model fitting was executed through non-linear multivariable regression techniques, with the minimum of the average coefficient of variation of the residuals (ACVR) serving as the objective function. The resulting fit of the kinetic model to the experimental data proved satisfactory, with an ACVR of less than 5 % across all instances. Notably, the maximum biodiesel productivity, obtained in this work, represented the highest value, compared to other related studies, using a fermented solid as a biocatalyst.

Dosiomics-based detection of dose distribution variations in helical tomotherapy for prostate cancer patients: influence of treatment plan parameters.

The stability of dosiomics features (DFs) and dose-volume histogram (DVH) parameters for detecting disparities in helical tomotherapy planned dose distributions was assessed. Treatment plans of 18 prostate patients were recalculated using the followings: field width (WF) (2.5 vs. 5), pitch factor (PF) (0.433 vs. 0.444), and modulation factor (MF) (2.5 vs. 3). From each of the eight plans per patient, ninety-three original and 744 wavelet-based DFs were extracted, using 3D-Slicer software, across six regions including: target volume (PTV), pelvic lymph nodes (PTV-LN), PTV + PTV-LN (PTV-All), one cm rind around PTV-All (PTV-Ring), rectum, and bladder. For the resulting DFs and DVH parameters, the coefficient of variation (CV) was calculated, and using hierarchical clustering, the features were classified into low/high variability. The significance of parameters on instability was analyzed by a three-way analysis of variance. All DF's were stable in PTV, PTV-LN, and PTV-Ring (average CV ( ≤0.36). Only one feature in the bladder ( =0.9), rectum ( =0.4), and PTV-All ( =0.37) were considered unstable due to change in MF in the bladder and WF in the PTV-All. The value of for the wavelet features was much higher than that for the original features. Out of 225 unstable wavelet features, 84 features had ≥1. The CVs for all the DVHs remained very small ( <0.06). This study highlights that the sensitivity of DFs to changes in tomotherapy planning parameters is influenced by the region and the DFs, particularly wavelet features, surpassing the effectiveness of DVHs.

Analytical performance specifications for trace elements in biological fluids derived from six countries federated external quality assessment schemes over 10 years.

This article defines analytical performance specifications (APS) for evaluating laboratory proficiency through an external quality assessment scheme. Standard deviations for proficiency assessment were derived from Thompson's characteristic function applied to robust data calculated from participants' submissions in the Occupational and Environmental Laboratory Medicine (OELM) external quality assurance scheme for trace elements in serum, whole blood and urine. Characteristic function was based on two parameters: (1) β- the average coefficient of variation (CV) at high sample concentrations; (2) α- the average standard deviation (SD) at low sample concentrations. APSs weredefined as 1.65 standard deviations calculated by Thompson's approach. Comparison between OELM robust data and characteristic function were used to validate the model. Application of the characteristic function allowed calculated APS for 18 elements across three matrices. Some limitations were noted, particularly for elements (1) with no sample concentrations near analytical technique limit of detection; (2) exhibiting high robust CV at high concentration; (3) exhibiting high analytical variability such as whole blood Tl and urine Pb; (4) with an unbalanced number of robust SD above and under the characteristic function such as whole blood Mn and serum Al and Zn. The characteristic function was a useful means of deriving APS for trace elements in biological fluids where biological variation data or outcome studies were not available. However, OELM external quality assurance scheme data suggests that the characteristic functions are not appropriate for all elements.

Comprehensive assessment of heavy metal pollution of agricultural soils impacted by the Kalsaka abandoned gold mine and artisanal gold mining in northern Burkina Faso.

In this study, the environmental quality of agricultural soils around the Kalsaka abandoned gold mine was evaluated. A total of 117 samples including industrial mine wastes, topsoil, and control soil were collected in and around the mine, and their heavy metal concentrations were determined using ICP-MS after aqua regia digestion. Except for Zn, the average concentrations of the metals were higher in mine wastes and the agricultural soils than their average upper continental crust (UCC) counterpart, whereas those of Ag, As, and Hg exceeded the UCC in the control soils. The control soils had the lowest contaminations and the lowest pollution levels for all metals except for Hg. Based on the average concentrations and coefficients of variation, it can be concluded that Cr, Ni, and Zn abundance in the agricultural soils was controlled by natural factors, whereas that of Ag, As, Hg, Co, Cu, and Mn was mainly associated with mining. The absence of Hg in industrial mine wastes and its high contents in agricultural and control soils reflected the artisanal gold mining source of this metal. Thus, single and integrated pollution indices showed that ecological risk and toxicity are much higher when Hg is included in the index calculation, suggesting cumulative effects of industrial and artisanal gold mining on the agricultural soil quality. The results also showed that Hg and As are the pollutants of major concern in the Kalsaka abandoned gold mine. Because of its proximity to human settlements, the Kalsaka abandoned gold mine necessitates an immediate rehabilitation.

Modeling Risk in Fusarium Head Blight and Yield Analysis in Five Winter Wheat Production Regions of Hungary

The five-year mean yield of five Hungarian wheat production counties was 5.59 t ha−1 with a 7.02% average coefficient of variation. There was a regional effect on yield when progressing from south to north with a 1–2 °C higher mean winter air temperature, meaning that the Ta in southern counties increased the five-season mean yield by 15.9% (p = 0.002) compared to the yield of northern counties. Logistic regression models developed to assess the FHB risk driven by a few meteorological variables (Ta; RH) provided proper predictive performance. The results in the regression model were validated against the measured infection rates (P%) provided by the NÉBIH 30 days before and after heading. The FHB pressure was comparatively higher in Zala County, probably due to its special topological and growing conditions, irrespective of the season. Across all areas studied, two of the five identified counties (Pest and Somogy) provided the best classification for FHB infection. In the remaining three counties, the seasonal mean prediction accuracy (differences) exceeded 10% in only 6 out of 30 model outputs. The modeled five-season P% values averaged 70.4% and 93.2% of the measured infection rates for models 1 and 2, respectively. The coincidence of wet and warm weather around the time of wheat flowering enhanced the risk of FHB.

Effects of parity, season of birth, and sex on within-litter variation and pre-weaning performance of F1 Large White × Landrace pigs.

A piglet's pre-weaning performance significantly influences both animal welfare and profitability in pig production. Understanding piglet pre-weaning performance influencing factors is key to enhancing animal welfare, reducing losses, and boosting profitability. The study aimed to evaluate the impact of parity, season of birth, and sex on within-litter variation and pre-weaning performance of F1 Large White × Landrace pigs. Information regarding total litter size, number of born alive, number of stillbirths, piglet weight at birth, mortality, and count of weaned F1 Large White × Landrace piglets was acquired from the farm database (April 2022-February 2023). 2602 females and 2882 males, a total of 5484 piglets were utilized, with records from 360 sows. The coefficient of variation (CV) of birth weights among piglets within a litter was calculated. The general linear model analysis in MiniTab 17 was used to evaluate the data, with Fisher's least significant difference test (p < 0.05) used for mean separation and Pearson's moment correlation coefficient calculated to assess relationships between survival rates, mortality rates, litter size, birth weight, and birth weight CV. Parity had a statistically significant impact on litter size, birth weight, and survival rate (p < 0.05). The sow's parity did not significantly (p > 0.05) impact the number of piglets born alive or weaned. Multiparous sows had a significantly larger litter size (p < 0.05) than primiparous sows at birth. The litter weights for parities 2, 4, and 5 did not significantly differ (p > 0.05), with averages of 20.95, 20.74, and 20.03 kg, respectively. About 91.29% was the highest survival rate recorded in parity 2 (p < 0.05). The 1st week of life recorded an 8.02% mortality rate. The mortality rate in parity 3-5 group was significantly (p < 0.05) higher (11.90%) in week 1 than in the other groups (parity 1: 6.79%, parity 2: 5.74%, parity 3-5: 8.54 and 9.21%). The litter sizes in autumn (17.34) and spring (17.72) were significantly larger (p < 0.05) than those in summer (16.47) and winter (16.83). In autumn and spring, the survival rate (83.15 and 85.84%, respectively) was significantly lower (p < 0.05) compared to summer (88.40%) and winter (89.07%). In all seasons, the litter weights did not significantly differ (p > 0.05). The birth weight CV was significantly (p < 0.05) lower during summer (20.11%) than during spring (22.43%), autumn (23.71%), and winter (21.69%). The season of birth had no significant effect (p > 0.05) on the number of live piglets. Males (1.34 kg) were heavier (p < 0.05) than females (1.30 kg) at birth. Notably, the birth weight CV was similar between males (22.43%) and females (22.52%). Litter size was positively correlated with average litter weight (rp = 0.576, p < 0.001), birth weight CV (rp = 0.244, p < 0.001), and mortality rate (rp = 0.378, p < 0.001). An insignificant relationship was observed between average litter weight and birth weight CV (rp = -0.028, p > 0.05) and survival rate (rp = -0.032, p > 0.05). In F1 Large White × Landrace pigs, birth uniformity among piglets declines as litter size grows larger. In parity 3-5, multiparous sows yield litters with reduced uniformity. With an increase in litter size, uniformity among piglets at birth worsens. A larger litter size and greater piglet birth weight variation are linked to a higher pre-weaning mortality rate. Producers need a balanced selection approach to boost litter size and must cull aging sows carefully to introduce younger, more productive females.