Coefficient Of Variation Values Research Articles

Homogeneity of the selected food mixes

The article presents the results of homogeneity assessments for selected food mixes based on computer image analysis. The study was conducted on müsli and condiment mixes standardly available on the consumer market. A total of 40 different ready-for-use products were analysed. Collected samples from three package of each product were placed in a special chamber and then photographed. Photographs were then subjected to computer image analysis to acquire information on the percentage content of individual components. Homogeneity assessment was based on the contents of a selected component called tracer and the coefficient of variation (CV). Lower CV values (3.02–27.31%) and thus better homogeneity was observed for condiment mixes as compared to müsli mixes (3.57–59.15%). Fourteen of twenty condiment mixes had adequate (acceptable at CV ≤ 10%) mixing degree. For the müsli, only six of the tested mixes had appropriate homogeneity. The presented results are a preliminary to developing an image-based methodology for determining the uniformity of granular dry food mixes.

Examination of the effects of COVID 19 on corneal endothelium.

PurposeTo demonstrate the effects of the disease on the corneal endothelium in individuals recovering from COVID-19 through specular microscopy.MethodsEighty individuals recovering from COVID-19 (group 1) and 72 healthy controls (group 2) were included in this prospective study. After examining visual acuity, refractive defect detection, anterior and posterior segment examinations, and specular microscopy measurements were calculated from images with at least 100 cells. The mean cell density (CD), mean coefficient of variation (CV), mean hexagonal cell percentage, mean cell area (AVG), and central corneal thickness (CCT) were evaluated.ResultsThe mean time from diagnosis of the disease in group 1 was 54.25 ± 6.36 days. The mean time elapsed since the PCR test became negative was 38.45 ± 6.87 days. Only four were treated in the hospital. Specular microscopy data showed that the CD was 2713.56 ± 246.25 and 2845.80 ± 299.27 in groups 1 and 2, respectively (p = 0.003). The CV values were 42.92 ± 6.79 and 40.16 ± 5.97, respectively (p = 0.009). The hexagonality were 46.51 ± 7.35 and 49.12 ± 6.87, respectively (p = 0.024). The AVG was 371.60 ± 34.64 and 353.16 ± 35.29, respectively (p = 0.007). The CCT values were 553.00 ± 73.2, and 526.84 ± 33.57, respectively (p = 0.005).ConclusionA decrease in the number of endothelial cells and hexagonal cells (polymorphism) as well as an increase in the cell area change coefficient (polymegatism) and the average cell area were observed from corneal specular microscopic examination of individuals recovering from COVID-19 in the early period of the disease. These results may be important in understanding the systemic effects of the disease.

Variability and Trend Analysis of the Rainfall of the Past 119 (1901-2019) Years using Statistical Techniques: A Case Study of Uttar Dinajpur, India

The present study aims to identify and measure the impact of climate change on rainfall patterns in the Uttar Dinajpur district of West Bengal. The hydro-meteorological time series rainfall data was collected from the IMD and CHRS data portals and subsequently analysed using various statistical methods. Agriculture in this district is the main economic activity, but the rainfall propensity is very unpredictable and sporadic that has a significant impact on agriculture. The rainfall results (1901-2019) were examined and assessed using statistical techniques for Mann-Kendall’s Z-statistic and Sen’s slope estimators. From the estimation, it is understood that the pre-monsoon, monsoon, and winter seasons have positive trends in rainfall, whereas the post-monsoon rainfall shows a negative trend and both Mann-Kendall and Sen’s slope projections depict the same. Likewise, January, February, April, May, June, July, August, and December reflect upward positive change, while a downward trend (decline trend) was recorded in March, September, and October. The winter Kharif crops are more impacted by this negative or decreasing pattern of seasonal rainfall than other crops. The maximum average monthly rainfall in July (892.1 mm) and January showed the lowest average monthly rainfall of 63.3 mm. The results revealed that during the monsoon season the maximum rainfall (75.2%) occurred and the coefficient of variance value is 20.4%. In the winter season, the minimal rainfall (2.87%) with a coefficient of variance (CV) is 72.9%. The rainfall forecast using SMOreg and linear regression methods has been calculated. This research contributes greatly to adopting different strategies by the planners, researchers, numerous government institutions, and NGOs for the overall development of the study area. This study may also be effective in the management of water resources in the study region.

Morphology-dependent resonances in laser-induced fluorescence images of micrometric gasoline/ethanol droplets utilizing the dye nile red.

The present study deals with the solvent-dependent morphology-dependent resonances (MDR) in the laser-induced fluorescence (LIF) signal of monodisperse gasoline droplets (30µm-60µm) generated with a droplet generator. To investigate the influence of an ethanol addition to gasoline and the respective LIF signal of the dye nile red dissolved in these fuel blends, a reference gasoline fuel is blended with various ethanol concentrations from E0 (gasoline) to E100 (pure ethanol). A spectral fluorescence characterization of the investigated fuel mixtures at various concentrations is carried out in a micro cell in order to identify the dye and ethanol concentration influence of the respective fuel mixtures. The absorption and emission spectra of the fuel mixtures show a Stokes shift with increasing ethanol concentration towards larger wavelengths. The coefficient of variation (COV) of the fluorescence signals of spherical droplets was utilized to characterize the MDR effects within the droplet LIF images. The investigations revealed an increase of MDR contribution in terms of the COV of LIF signals with larger droplet diameters. For small droplets, no monotonic trend was found for contribution of MDR in the LIF signal as a function of the ethanol concentration. For larger droplets (e.g., 50µm-60µm), a lower contribution of MDR in LIF signals was observed with increasing ethanol content. For E80 and most of the studied ethanol blends, the normalized integrated COV values exhibited maxima at certain droplet sizes (40µm, 47.5µm, and 55µm), which indicate the presence of distinct MDR effects.

Risk Analysis of Rice Farming in Polenga Village, Watubangga District, Kolaka Regency

This study aims to determine the amount of production risk, cost risk and income risk of rice farmers in Polenga Village, Watubangga District, Kolaka Regency. The basic method used in this research is quantitative descriptive. Determination of the research sample using simple random sampling method, with a total sample of 48 rice farmers. The results of this study are the risks faced by farmers in Polenga Village, Kecamtan Watubangga, which is the production risk, costs risk and income risk. Based on the value of variation coefficients (CV) obtained, if CV 0.5 then the production risk , costs and farm income borne by farmers is greater, while the value of CV ≤ 0.5, the farmer will always profit or break even. At the production risk , the coefficient of variation (CV) was obtained at 0.1 ≤ 0.5 indicate that the farm production risk that burdened by farmers is low. Cost risk obtained by the value of the Coefficient of Variation (CV) of 0.2 ≤ 0.5 indicates that the farm cost risk that burdened by farmers is low and the farm income risk is obtained a value of Variation Coefficient(CV) of 0.1 ≤ 0.5 indicates that burdened by farmers is low too.

608-P: Relationship between Time-in-Range and Estimated HbA1c Derived from Continuous Glucose Monitoring System in Adults with Type 1 Diabetes Mellitus

Aims: Time-in-range (TIR) and estimated glycated hemoglobin (eHbA1c), two key metrics derived from continuous glucose monitoring system (CGMS), are valuable for glycemic control. This study is to investigate the relationship between TIR and eHbA1c, and the impact of glycemic variability on their relationship. Methods: The CGMS data were collected from baseline and follow-up visits in a clinical trial (NCT03522870) and yearly visits in the Guangdong Type 1 Diabetes Translational Medicine Study. Adult patients with type 1 diabetes (≥18 yrs) who had available CGM data for > 3 days were included. Correlation between TIR and eHbA1c was explored according to different stratification of glycemic variability assessed by glucose coefficient of variation (CV). Predicted TIR in the fixed eHbA1c value was calculated via the linear regression equations performed in the respective interquartile group of CV. Results: From March 2014 to July 2020, a total of 260 CGMS data were collected. The mean wearing time of available CGM data was 11.8±3.8 days, and the mean value of TIR, eHbA1c, and CV was 62.9±14.1%, 7.2±0.8%, and 39.4±8.1%, respectively. There was a strong negative correlation between TIR and eHbA1c (R=-0.83, P<0.001). For patients with stable glycemic variability (CV<36%), the correlation between the two metrics was stronger (R=-0.95) while in the unstable group the coefficient was decreased (R=-0.80). Based on the regression equations, the predicted %TIR value was decreased across the ascending quartiles with 73.0% in the lowest quartile of CV (<25th quartile, <33.8%), 67.4% in 25th - 50th quartile (33.8-39.2%), 61.4% in 50th - 75th quartile (39.2-44.9%) and 58.5% in the highest quartile (>75th quartile, CV >44.9%) when eHbA1c was set as 7%. Conclusions: There is a strong correlation between TIR and eHbA1c in adult patients with type 1 diabetes. Patients with lower glycemic variability usually have higher %TIR in the same eHbA1c level. Disclosure Y. Zhou: None. J. Weng: None. H. Liu: None. D. Yang: None. H. Ai: None. J. Lv: None. X. Mai: None. W. Xu: None. B. Yao: None. J. Yan: None. Funding National Key Research and Development Program of China (2017YFC1309600)

Automatic Image Selection Model Based on Machine Learning for Endobronchial Ultrasound Strain Elastography Videos

BackgroundEndoscopic ultrasound (EBUS) strain elastography can diagnose intrathoracic benign and malignant lymph nodes (LNs) by reflecting the relative stiffness of tissues. Due to strong subjectivity, it is difficult to give full play to the diagnostic efficiency of strain elastography. This study aims to use machine learning to automatically select high-quality and stable representative images from EBUS strain elastography videos.MethodsLNs with qualified strain elastography videos from June 2019 to November 2019 were enrolled in the training and validation sets randomly at a quantity ratio of 3:1 to train an automatic image selection model using machine learning algorithm. The strain elastography videos in December 2019 were used as the test set, from which three representative images were selected for each LN by the model. Meanwhile, three experts and three trainees selected one representative image severally for each LN on the test set. Qualitative grading score and four quantitative methods were used to evaluate images above to assess the performance of the automatic image selection model.ResultsA total of 415 LNs were included in the training and validation sets and 91 LNs in the test set. Result of the qualitative grading score showed that there was no statistical difference between the three images selected by the machine learning model. Coefficient of variation (CV) values of the four quantitative methods in the machine learning group were all lower than the corresponding CV values in the expert and trainee groups, which demonstrated great stability of the machine learning model. Diagnostic performance analysis on the four quantitative methods showed that the diagnostic accuracies were range from 70.33% to 73.63% in the trainee group, 78.02% to 83.52% in the machine learning group, and 80.22% to 82.42% in the expert group. Moreover, there were no statistical differences in corresponding mean values of the four quantitative methods between the machine learning and expert groups (p >0.05).ConclusionThe automatic image selection model established in this study can help select stable and high-quality representative images from EBUS strain elastography videos, which has great potential in the diagnosis of intrathoracic LNs.

Regional characteristics and discrimination of the fermentation starter Hong Qu in traditional rice wine brewing

SummaryHong Qu (HQ) is a fermentation starter used to brew Hong Qu rice wine (HQ wine). The regional characteristics and discrimination of HQ are not fully understood. This study elucidates fermentation characteristics of HQ through sensory evaluation and the analysis of six physicochemical characteristics of HQ wine brewed by twenty‐nine HQ from different regions. Results showed that the complex physicochemical indices of HQ wine would be reduced to three principal components – total acidity, total sugars and non‐sugar solids by principal component analysis. Twenty‐nine HQ samples were classified into four clusters by hierarchical cluster analysis – Cluster A, B, C and D. Cluster B only included Gutian HQ (GTQ) brewing base liquors with a fresh and soft taste, the highest sensory scores and low coefficient of variation (CV). The rest three Clusters mainly included Wuyi HQ (WYQ) brewing base liquors with full‐bodied and tasteful flavours, high CV values and different sensory scores. WYQ could brew more good and less below standard liquors, while the quality of HQ wine brewed using GTQ was more even than that of WYQ. Conclusively, the geographical location and processing technology of HQ are the main external factors contributing to the regional characteristics of HQ wine.

Amplification-free Detection of Cytomegalovirus miRNA Using a Modification-free Surface Plasmon Resonance Biosensor.

Cytomegalovirus (CMV) is the most frequent cause of congenital infection worldwide; congenital CMV may lead to significant mortality, morbidity, or long-term sequelae, such as sensorineural hearing loss. The current study presents a newly designed surface plasmon resonance (SPR) biosensor for CMV-specific microRNAs that does not involve extra care for receptor immobilization or treatment to prevent fouling on bare gold surfaces. The modification-free approach, which utilizes a poly-adenine [poly(A)]-Au interaction, exhibited a high affinity that was comparable to that of the gold-sulfur (Au-S) interaction. In addition, magnetic nanoparticles (MNPs) were used to separate the analyte from complex sample matrixes that significantly reduced nonspecific adsorption. Moreover, the MNPs also played an important role in SPR signal amplification due to the binding-induced change in the refractive index. Our SPR biosensing platform was used successfully for the multi-detection of the microRNAs, UL22A-5p, and UL112-3p, which were associated with CMV. Our SPR biosensor offered the detection limits of 108 fM and 24 fM for UL22A-5p and UL112-3p, respectively, with an R2 of 0.9661 and 0.9985, respectively. The precision of this biosensor has an acceptable CV (coefficient of variation) value of <10%. In addition, our sensor is capable of discriminating between serum samples collected from healthy and CMV-infected newborns. Taken together, we believe that our newly developed SPR biosensing platform is a promising alternative for the diagnosis of CMV-specific microRNA in clinical settings, and its application for the detection of other miRNAs may be extended further.

Repeatability of Spectral Domain Optical Coherence Tomography Measurements of Bruch's Membrane Opening-Minimum Rim Width in Epiretinal Membrane Patients with Peripapillary Involvement.

The Bruch’s membrane opening-minimum rim width (BMO-MRW) is a recently introduced parameter of the neuroretinal rim. We analyzed the repeatability of spectral-domain optical coherence tomography (SD-OCT) measurements of BMO-MRW in epiretinal membrane (ERM) patients with peripapillary involvement, since the surface around the optic disc is distorted in such patients. BMO-MRW and retinal nerve fiber layer (RNFL) thickness measurements were performed using SD-OCT in prospectively enrolled ERM patients and age-matched healthy control individuals. After two consecutive measurements with a 5 min interval, repeatability was analyzed using the intraclass correlation coefficient (ICC), repeatability coefficient (RC), and coefficient of variation (CV). Fifty-two eyes of 52 ERM patients and 62 eyes of 62 healthy controls were included in the study. The ICCs of the mean BMO-MRW/RNFL thickness measurements were 0.999/0.985 in ERM eyes and 0.999/0.999 in normal eyes, respectively. The RC values of mean BMO-MRW/RNFL thickness measurements were 9.0/6.25 μm in ERM eyes and 4.61/0.92 μm in normal eyes, respectively. The CV values were 0.91% and 1.45% for BMO-MRW and RNFL thickness in ERM eyes, and 0.63% and 0.33% in normal eyes, respectively. In ERM eyes, the RC, CV of average BMO-MRW were 1.9 and 1.4 times greater than those of normal eyes, but 6.8 and 4.4 times greater for average RNFL thickness. BMO-MRW and RNFL thickness showed good repeatability in the diseased eyes with peripapillary involvement and healthy control eyes. Based on the ICC, RC, and CV values, the repeatability of BMO-MRW measurements in peripapillary membrane patients was better than that of RNFL thickness.

Shrink, weighing accuracy, and weighing precision of mineral supplement in five commercial dairies in the Western United States.

Shrink, accuracy, and precision of ingredient weighing are critical factors of efficiency in TMR-fed dairy systems. Those factors have been evaluated for major feeds; however, we are not aware of any reports for mineral supplement. Farms commonly mix mineral supplement with other low-inclusion ingredients into a premix which is used later as a single ingredient for TMR formulation. Our objectives were to evaluate shrink, weighing accuracy, and weighing precision of mineral supplement during premix formulation, and variation in concentration of minerals in mineral supplement and TMR, in five large dairies in the Western United States. We used the automated weight-tracking system at each farm to account for all the mineral supplement loaded into the mixing-wagon and collected samples of mineral supplement and TMR from time of mineral supplement delivery at the farm until 100% of it was consumed. Mean, standard deviation and coefficient of variation (CV) for each variable were calculated with SAS 9.4. Average shrink was estimated at 2.0% for mineral supplement during storage and loading, ranging from 0.37% to 3.25%. Mineral supplement weighing deviation from the targeted amount was 1.54% on average for the five dairies with a 95% CV. Mineral composition of mineral supplements averaged 11.3%, 0.27%, and 3.16% for Ca, P, and Mg, and 215, 881, and 1533 ppm for Cu, Mn, and Zn, respectively. Mineral compositions in TMR averaged 0.84%, 0.41%, and 0.37% for Ca, P, and Mg, respectively; and 15.1, 71, and 94.5 ppm for Cu, Mn, and Zn, respectively. The CV of all minerals except Ca, were larger for mineral supplement than TMR, and with the exception of P in mineral supplement, CV of trace minerals were larger than CV values for macro minerals. Our shrink estimates for mineral supplement represent an initial approximation to this issue. Results of our weighing deviation analysis suggest some room for improvement on the precision of weighing mineral supplement at the time when premix is prepared at the farm, which could improve consistency in chemical composition of the premix and consequently reduce the variation (CV values) of mineral concentrations in TMR.

ANALISIS PENDAPATAN DAN RISIKO USAHATANI CABAI MERAH DI KECAMATAN WAY SULAN KABUPATEN LAMPUNG SELATAN

This research aims to assess the income of red chili farming, the amount of risk faced by red chili farmers, and the correlation between risk and income accepted by the red chili farmers. The study was conducted in Way Sulan Sub-district of South Lampung Regency. The total samples were 56 farmers drawn using a simple random sampling method. The data were collected in March - April 2019 using questionnaires. The first aim was analyzed using the revenue-cost ratio (R/C), which is the comparison between total revenue and total cost. The second aim was analyzed by risk analysis using coefficient variation (CV) and the lower limit (L) on five planting seasons. The third aim was analyzed by Product Moment Pearson correlation. This research results showed that the red chili farming income was profitable because of R/C &gt;1. Risk calculation on five planting seasons results showed that the value of CV&lt;0,50 and L&gt;0, meaning that red chili farming was still profitable in any level of risk. There was positive correlation between the amount of risk and income. It means that the higher level of expected income, the higher level of risk received by farmers. Key words: income, red chili, risk

Quantitative Analyses of Foot Processes, Mitochondria, and Basement Membranes by Structured Illumination

IntroductionFoot process effacement and mitochondrial fission associate with kidney disease pathogenesis. Electron microscopy is the gold-standard method for their visualization, but the observable area of electron microscopy is smaller than light microscopy. It is important to develop alternative ways to quantitatively evaluate these microstructural changes because the lesion site of renal diseases can be focal.MethodsWe analyzed elastica-Masson trichrome (EMT) and periodic acid-Schiff (PAS) stained kidney sections using structured illumination microscopy (SIM).ResultsEMT staining revealed three-dimensional (3D) structures of foot process, whereas ponceau xylidine acid fuchsin azophloxine solution induced fluorescence. Conversion of foot process images into their constituent frequencies by Fourier transform showed that the concentric square of (1/4)2-(1/16)2 in the power spectra (PS) included information for normal periodic structures of foot processes. Foot process integrity, assessed by PS, negatively correlated with proteinuria. EMT-stained sections revealed fragmented mitochondria in mice with mitochondrial injuries and patients with tubulointerstitial nephritis; Fourier transform quantified associated mitochondrial injury. Quantified mitochondrial damage in patients with immunoglobulin A (IgA) nephropathy predicted a decline in estimated glomerular filtration rate (eGFR) after kidney biopsy but did not correlate with eGFR at biopsy. PAS-stained sections, excited by a 640 nm laser, combined with the coefficient of variation values, quantified subtle changes in the basement membranes of patients with membranous nephropathy stage I.ConclusionsKidney microstructures are quantified from sections prepared in clinical practice using SIM.

A semiautomated method to quantitatively assess osteolytic lesion volume and bone mineral density within acetabular regions of interest from CT.

The objectives of this study were to (1) develop a semiautomated method to obtain lesion volume and bone mineral density (BMD) in terms of Hounsfield units from pelvic computed tomography (CT) scans in three regions of interest, and (2) assess accuracy and reliability of the method based on cadaveric CT scans. Image artefacts due to metal implants reduce CT clarity and are more severe with more than one implant in situ. Therefore, accuracy and reliability tests were performed with varying numbers of total hip arthroplasties implanted. To test the accuracy of lesion size measurements, microcomputed tomography was used as a reference. Mean absolute error ranged from 36 to 284 mm3 after five measurements. Intra- and inter-operator reliability of the entire method was measured for a selection of parameters. All coefficient of variation values were good to excellent for CT scans of the native pelvic anatomy and a CT scans of the same pelvis with one and two implants in situ. Accuracy of quantifying lesion volume decreased with decreasing CT image clarity by 0.6%-3.6% mean absolute relative error. Reliability of lesion volume measurement decreased with decreasing CT clarity. This was also the case for reliability of BMD measurements in the region most disrupted by metal artefact. The presented method proposes an approach for quantifying bone loss which has been proven to be accurate, reliable, and clinically applicable.

Evaluating NISAR's cropland mapping algorithm over the conterminous United States using Sentinel-1 data

Accurate knowledge of the distribution, breadth and change in agricultural activity is important to food security and the related trade and policy mechanisms. Routine observations afforded by spaceborne Synthetic Aperture Radar (SAR) allows for high-fidelity monitoring of agricultural parameters at the field scale. Here we evaluate the approach to be used for generating NASA's upcoming NASA ISRO SAR (NISAR) mission's L-band cropland product using Sentinel-1C-band data. This study uses all ascending Sentinel-1A/B data collected over the conterminous United States in 2017 to compute the coefficient of variation (CV) at 150 m × 150 m resolution and evaluates the overall accuracy (OA) of CV-based crop/non-crop classifications at 100 one-by-one degree tiles. We calculate accuracies using two approaches: (a) using a literature-recommended constant CV threshold of 0.5 (CVthr_0.5) and (b) determining optimal CV thresholds for every tile using Youden's J statistic (YJS), CVthr_YJS. These accuracy comparisons are important for determining (1) the viability of using a computationally inexpensive and straightforward approach for cropland classification over large spatial scales/diverse land covers (i.e., can accuracies ≥80% be routinely achieved?), (2) how closely OA0.5 compares to the performance ceiling (OAYJS). This information will help determine whether approach (a) is appropriate and how much potential room of improvement there could be in modifying it. Results for OA0.5 and OAYJS are 81.5% and 86.8%, respectively. A breakdown by census geographic region, showed that OA0.5 (OAYJS) exceeded 80% (90%) in the South and Midwest, but was only 76.1% (73.5%) in the West. The improvement in OAYJS mainly stems from tiles with >40% crop prevalence having about 10% greater OA values. To better examine the potential of the approach for land cover classification, results of approach (b) were also stratified by crop. Approach (b) accurately detected most non-crop classes as non-crop (>80%), but with low OAYJS values for grasslands/pasture, especially in the West. CV values for crop were distinct from non-crop indicating that the approach is suitable for crop/non-crop classifications. Because results CV values have substantial overlap within crop/non-crop classes, indicating the approach is poorly suited for land cover classifications. We also detected a strong geographic dependence of CVthr_YJS: values ranged from about 0.2 at the coasts and gradually increase to about 0.6 in the Central United States, most often falling close to 0.3 and 0.5.

Implications of intra-plot heterogeneity for yield estimation accuracy: Evidence from smallholder maize systems in Ethiopia.

Intra-plot heterogeneity in yield is often observed in smallholder farming systems, although its implications for yield measurement remain under-investigated. Using a unique dataset on smallholder maize production in Ethiopia, we quantify the magnitude of inter- and intra-plot heterogeneity, describe the relationship between intra-plot heterogeneity and maize productivity, and document the implications of intra-field heterogeneity on the accuracy of alternative yield estimation protocols. Our data include five common yield estimation protocols, as well as full plot harvests of 230 smallholder maize fields. We surveyed agronomic decisions, biophysical variables, and accessibility characteristics of the surveyed fields. We quantify intra-plot heterogeneity using the coefficient of variation (CV) of stand density, cob weight, and maize grain yield. A generalized linear mixed model is used to explore the relationship between these variables and the method- and heterogeneity-dependence of yield estimation accuracy. We find inter-plot CV values ranging from 32 to 56 %, 22 to 73 % and 39 to 49 % in population density, cob weight and grain yield, respectively. Intra-plot heterogeneity constituted most of this variation, with across-method mean CV values of 41 %, 82 % and 63 %, respectively, of the total variability in population density, cob weight and grain yield. A rise in intra-plot heterogeneity of 0.5 % to 0.8 % is associated with a significant increase in yield estimation error under alternative yield estimation protocols. Regression analysis shows that interactions in agronomic decisions, input intensity and plot accessibility factors dictate intra-plot heterogeneity and method accuracy in smallholder systems. Intra-plot heterogeneity is larger than inter-plot heterogeneity in the current study area. Our analysis shows that the effect of intra-plot heterogeneity on yield estimation accuracies is method-dependent and yield estimation methods that fail to capture true intra-plot heterogeneity are more error-prone. Results of such estimations should be considered with caution when used as the basis of decision-making.

Characterization of Lactation Curve Patterns using Non-linear Models in Crossbred Dairy Cattle

Background: Lactation curve patterns are currently integrated in dairy cow’s management software. Lactation curve modeling is useful for monitoring individual yields for diet planning, determining optimum strategies for insemination and genetic evaluation. It also helps for predicting expected missing values on field records and gives concise summary of biological efficiency and persistency of dairy cows.Methods: The study was aimed to characterize the lactation curve pattern for crossbred dairy cattle using different non-linear models. During the period 1991 to 2018, daily milk yield (DMY) consisted of 281698 records of 750 crossbred dairy cows maintained at Livestock Farms. GADVASU, Ludhiana, were collected for the study. Different non-linear models viz. exponential decline function (EDF), parabolic exponential model (PEM), inverse polynomial model (IPM), gamma-type function (GTF), mixed log function (MLF) and Ali and Schaeffer model (ASF) were used for the analysis. The model(s) that best fit and describe the curve characteristics was selected on the basis of coefficient of determination (R2), coefficient of variation (CV), Akaike information criterion (AIC) and mean square error (MSE).Result: The study clearly revealed that the PRM gave highest fit to DMY data with R2, MSE, AIC and CV values of 98.10%, 0.087, -743.31 and 2.37%, respectively. The IPM had also best fitted the observed DMY data with highest R2 (98.05%), lower MSE (0.089), low AIC (-735.8972) and lower CV (2.40%) values. The fitting of observed DMY data with predicted DMY were also found to be higher in the MLF (R2= 96.46%, MSE= 0.159, AIC= -558.16 and CV= 3.21%) and GTF (R2= 95.85%, MSE= 0.190, AIC= -505.24 and CV= 3.50%), whilst the EDF and PEM Models depicted relatively low fit to the DMY data when compared with the other non-linear models. However, IPM and GTF models can be used for accurate prediction of daily milk yield in the crossbred cattle population because they were typical standard lactation curves.

ANALYSIS OF FACTORS RELATING TO DAY-TO-DAY HOME BLOOD PRESSURE VARIATION IN HYPERTENSIVE PATIENTS

Objective: In order to prevent cardiovascular events and organ injuries in hypertensive patients, strict blood pressure (BP) control over 24 hours is of primary importance. In addition to the BP level, it has been indicated that the variabilities of blood pressure during a day or between visits also influence the risk of cardiovascular disorders. This study aimed to delineate the factors relating to the variations of office and home BPs throughout a year in hypertensive outpatients under antihypertensive therapy. Design and method: The subjects enrolled in this study were 83 hypertensive out-patients who recorded home blood pressure measurements. Office BP and the home BP records within 7 days before each visit were collected for the analyses calculating the coefficient of variation (CV). In addition to the physical findings such as blood pressure and body mass index, laboratory data of blood and urine samples were collected. Results: The office BP value (131/77mmHg) was comparable to the morning home BP (130/76) and higher than the evening home BP (126/73), however, the CV values were comparable between the office and the morning and evening home BPs. Correlations of BP and CV were stronger between the morning and the evening home BPs than between the office and the home BPs. The CV of systolic office BP was greater in patients with diabetes mellitus than patients without diabetes (7.8 vs 6.1%). In patients with chronic kidney disease, the CVs of diastolic office BP and diastolic evening home BP were greater than patients without chronic kidney disease (8.0 vs 6.2% and 8.1 vs 6.7%, respectively). In addition, The CVs of diastolic morning and evening home BP were positively correlated with serum creatinine and negatively correlated with estimated glomerular filtration rate. Patients with cardiovascular diseases such as stroke and coronary artery disease showed greater CV of diastolic morning home BP than patients without cardiovascular diseases (8.2 vs 6.6%). Conclusions: These results suggest that the home BP exhibits different variability from the office BP and the BP variability is increased in high-risk hypertensive patients with diabetes mellitus, chronic kidney disease and cardiovascular diseases.

Dynamics of cerebral perfusion and oxygenation parameters following endovascular treatment of acute ischemic stroke

BackgroundWe studied the effects of endovascular treatment (EVT) and the impact of the extent of recanalization on cerebral perfusion and oxygenation parameters in patients with acute ischemic stroke (AIS) and...

Establishment of an analytical method for simultaneous quantitation of CDK4/6 inhibitors, aromatase inhibitors, and an estrogen receptor antagonist in human plasma using LC-ESI-MS/MS

Cyclin-dependent kinase 4 and 6 (CDK4/6) inhibitors (palbociclib, abemaciclib, and ribociclib) are used to treat human epithelial growth factor receptor (HER)-2 negative and hormone receptor (HR) positive advanced breast cancer in combination with aromatase inhibitors (letrozole, anastrozole) or an estrogen receptor antagonist (fulvestrant). Administration of these drugs frequently causes severe side effects, such as neutropenia and diarrhea. Therefore, therapeutic drug monitoring (TDM) of CDK4/6 inhibitors, aromatase inhibitors, and the estrogen receptor antagonist is considered important for ensuring the efficacy and safety of these drugs. In this study, we describe a simple, highly sensitive, and specific liquid chromatography/electrospray ionization tandem mass spectrometry method for simultaneous quantitation of the concentrations of palbociclib, abemaciclib, ribociclib, letrozole, anastrozole, and fulvestrant. In addition, we analyzed plasma samples from patients with HER2-negative and HR-positive advanced breast cancer treated with these compounds using this novel method. In our method, the intra-assay relative error (RE) values ranged from −12.8% to 12.9%, the inter-assay RE values ranged from −4.8% to 6.2%, and the coefficient of variation (CV) values for intra- and inter-assay were ≤8.6% and ≤13.3%, respectively. The analytes showed good stability with RE values ranging from −13.5% to 13.6% and CV values <10.4%. Moreover, all the samples from patients were successfully quantified, and were within the range of measurement. This method can be used for TDM of routine anticancer drugs in clinical practice and for pharmacokinetics/pharmacodynamics research in future studies.