Validating post-enrichment steps in environmental RNA analysis for improving its availability from water samples.

Environmental RNA (eRNA) analysis is expected to inclusively provide the physiological information of a population and community without individual sampling, having the potential for the improved monitoring of biodiversity and ecosystem function. Protocol development for maximizing eRNA availability is crucial to interpret its detection and quantification results with high accuracy and reliability, but the methodological validation and improvement of eRNA collection and processing methods are scarce. In this study, the technical steps after eRNA extraction, including genomic DNA (gDNA) removal and reverse transcription, were focused on and their performances were compared by zebrafish (Danio rerio) aquarium experiments. Additionally, this study also focused on the eRNA quantification variabilities between replicates and compared them between the PCR and sample levels. Results showed that (i) there was a trade-off between gDNA removal approaches and eRNA yields and an excess gDNA removal could lead to the false-negative eRNA detection, (ii) the use of the gene-specific primers for reverse transcription could increase the eRNA yields for multiple mitochondrial and nuclear genes compared with the random hexamer primers, and (iii) the coefficient of variation (CV) values of eRNA quantifications between PCR replicates were substantially lower for those between samples. Including the study, further knowledge for the sensitive and precise detection of macro-organismal eRNA should be needed for increasing the reliability and robustness of eRNA-based biomonitoring.

Pooling of intra-site measurements inflates variability of the correlation between environmental DNA concentration and organism abundance.

Environmental DNA (eDNA) analysis can promote efficient ecosystem monitoring and resource management. However, limited knowledge of the factors affecting the relationship between eDNA concentration and organism abundance causes uncertainty in relative abundance estimates based on eDNA concentration. Pooling of data points obtained from multiple locations within a site has been used to mitigate intra-site variation in eDNA and abundance estimates, but decreases the sample size used for estimating the relationship. I here assessed how the pooling of intra-site measurements of eDNA concentration and organism abundance impacted the reliability of the correlative relationship between eDNA concentration and organism abundance. Mathematical models were developed to simulate measurements of eDNA concentrations and organism abundances from multiple locations in a given survey site, and the CVs (coefficient of variability) of the correlations were compared depending on whether data points from different locations were individually treated or pooled. Although the mean and median values of the correlation coefficients were similar between the scenarios, the CVs of the simulated correlations were substantially higher under the pooled scenario than the individual scenario. Additionally, I re-analyzed two empirical studies conducted in lakes, both showing higher CVs of the correlations by pooling intra-site measurements. This study suggests that it would make eDNA-based abundance estimation more reliable and reproducible to individually analyze target eDNA concentrations and organism abundance estimates.

Tacrolimus variability is associated with de novo donor-specific antibody development in pediatric renal transplant recipients.

BACKGROUND: Donor-specific antibody (DSA) is a risk factor for antibody-mediated rejection and shortened graft survival. We investigated the role of intrapatient variability in tacrolimus trough levels on graft outcomes (i.e., de novo DSA, rejection, graft loss) in pediatric renal transplant recipients. METHODS: This was a single-center retrospective study which included 38 pediatric renal transplant recipients. Intrapatient tacrolimus variability was defined using the coefficient of variation (CV; SD/Mean × 100) for all levels obtained after 3 months post-transplant. CV cut-points of 30%, 40%, and 50% were used in the analyses. RESULTS: The median CV 43.1% (35.0%, 58.6%). Out of 38 patients, 19 (50%) developed de novo DSA. In the logistic regression model, after adjusting for age, rejection history, maintenance immunosuppression, and CV, for every 10% increase in tacrolimus variability, the odds of developing de novo DSA increased by 53% (p = 0.048, CI 1.0005, 1.11). Age at transplant was also an independent risk factor for DSA development; every 1 year increase in age was associated with a 31% increase in the odds of developing DSA (p = 0.03, CI 1.03, 1.67). At a CV cut-point ≥ 30%, higher tacrolimus variability was associated with an increased incidence of allograft rejection (0% vs 42%, < 30 and ≥ 30% respectively, p = 0.07). As there were few graft loss events (n = 4) in our study population, an association could not be determined between tacrolimus variability and graft loss. CONCLUSION: Tacrolimus variability and age at transplant were identified as independent risk factors for de novo DSA development. There was an association between tacrolimus variability and rejection in pediatric renal transplant recipients. Adding the assessment of tacrolimus variability to current monitoring methods may be an important step towards improving graft outcomes.

[Consideration on SNR in Synthetic MRI].

Synthetic magnetic resonance imaging (MRI) can create different contrast weighted images by quantifying the T1, T2, and proton density values of the subjects from a single series of scan data. It has not been clarified how the signal to noise ratio (SNR) of the synthesized image varies depending on imaging parameters. We investigated the change of SNR in synthesized MR images by the experiment using self-made phantom. The SNR ratio of synthesized image by synthetic MRI showed the same tendency as the theoretical values due to parameter change in Ny, Nx, slice thickness, number of excitations. However, as for BW, the SNR ratio tended to be different from the theoretical values in some cases. In addition, it was suggested that the SNR of the composite image has relevance to the quantitative accuracy of the T1, T2, and proton density values. We thought that this is due to the image acquisition process by synthetic MRI.

Biological Variability of Estimated GFR and Albuminuria in CKD.

RATIONALE & OBJECTIVE: Determining whether a change in estimated glomerular filtration rate (eGFR) or albuminuria is clinically significant requires knowledge of short-term within-person variability of the measurements, which few studies have addressed in the setting of chronic kidney disease. STUDY DESIGN: Cross-sectional study with multiple collections over less than 4 weeks. SETTING & PARTICIPANTS: Clinically stable outpatients with chronic kidney disease (N=50; mean age, 56.8 years; median eGFR, 40mL/min/1.73m2; median urinary albumin-creatinine ratio (UACR), 173mg/g). EXPOSURE: Repeat measurements from serially collected samples across 3 study visits. OUTCOMES: Measurements of urine albumin concentration (UAC), UACR, and plasma creatinine, cystatin C, ß2-microglobulin (B2M), and beta trace protein (BTP). ANALYTICAL APPROACH: We calculated within-person coefficients of variation (CVw) values and corresponding reference change positive and negative (RCVpos and RCVneg) values using log-transformed measurements. RESULTS: Median CVw (RCVpos; RCVneg) values of filtration markers were 5.4% (+16%; -14%) for serum creatinine, 4.1% (+12%; -11%) for cystatin C, 7.4% (+23%; -18%) for BTP, and 5.6% (+17%; -14%) for B2M. Results for albuminuria were 33.2% (+145%; -59%) for first-morning UAC, 50.6% (+276%; -73%) for random spot UAC, 32.5% (+141%; -58%) for first-morning UACR, and 29.7% (124%; -55%) for random spot UACR. CVw values for filtration markers were comparable across the range of baseline eGFRs. CVw values for UAC and UACR were comparable across the range of baseline albuminuria values. LIMITATIONS: Small sample size limits the ability to detect differences in variability across markers. Participants were recruited and followed up in a clinical and not research setting, so some preanalytical factors could not be controlled. CONCLUSIONS: eGFR markers appear to have relatively low short-term within-person variability, whereas variability in albuminuria appears to be high, making it difficult to distinguish random variability from meaningful biologic changes.

Analysis of inter-/intra-E-plate repeatability in the real-time cell analyzer.

Over the past decade, the real-time cell analyzer (RTCA) has provided a good tool to the cell-based in vitro assay. Unlike the traditional systems that label the target cells with luminescence, fluorescence, or light absorption, RTCA monitors cell properties using noninvasive and label-free impedance measuring. However, realization of the maximum value of RTCA for applications will require assurance of within-experiment repeatability, day-to-day repeatability, and robustness to variations in conditions that might occur from different experiments. In this article, the performance and variability of RTCA is evaluated and a novel repeatability index (RI) is proposed to analyze the intra-/inter-E-plate repeatability of RTCA. The repeatability assay involves six cell lines and two media (water [H2O] and dimethyl sulfoxide [DMSO]). First, six cell lines are exposed to the media individually, and time-dependent cellular response curves characterized as a cell index (CI) are recorded by RTCA. Then, the variations along sampling time and among repeated tests are calculated and RI values are obtained. Finally, a discriminating standard is set up to evaluate the degree of repeatability. As opposed to the standardized methodologies, it is shown that the presented index can give the quantitative evaluation for repeatability of RTCA within E-plate and variation on different days.

The estimation of calibration equations for variables with heteroscedastic measurement errors.

In clinical chemistry and medical research, there is often a need to calibrate the values obtained from an old or discontinued laboratory procedure to the values obtained from a new or currently used laboratory method. The objective of the calibration study is to identify a transformation that can be used to convert the test values of one laboratory measurement procedure into the values that would be obtained using another measurement procedure. However, in the presence of heteroscedastic measurement error, there is no good statistical method available for estimating the transformation. In this paper, we propose a set of statistical methods for a calibration study when the magnitude of the measurement error is proportional to the underlying true level. The corresponding sample size estimation method for conducting a calibration study is discussed as well. The proposed new method is theoretically justified and evaluated for its finite sample properties via an extensive numerical study. Two examples based on real data are used to illustrate the procedure.

Association between fasting plasma glucose variability and maternal and infant outcomes in patients with hyperglycemia during pregnancy: a retrospective cohort study.

Background: Blood glucose variability (GV) is believed to be closely related to the occurrence of adverse obstetric outcomes. However, few studies have investigated how the change in fasting plasma glucose (FPG) influenced on the adverse obstetric outcomes. This study mainly evaluated the relationship between FPG coefficient of variation (FPG-CV) and adverse outcomes in patients with gestational hyperglycemia and determine the ideal FPG-CV threshold for predicting maternal and infant outcomes. Methods: We retrospective analyzed the data of 608 pregnant hyperglycemic patients in the Obstetrics Department of Shengjing Hospital Affiliated to China Medical University between June 2019 and December 2021 and followed up inpatients through the Hospital Information System (HIS). We collected the venous FPG from 24-28 weeks of pregnancy to delivery. Maternal and infant outcomes were based on the latest definitions. The chi-square test and logistic regression analysis were performed to evaluate the correlation between FPG-CV and adverse outcomes. Two multivariate binary logistic regression models were used to adjust for confounding factors. Stratified analysis was performed according to hemoglobin A1c (HbA1c) levels (<5.9% and ≥5.9%) and insulin injection (not used and used) in the third trimester of pregnancy. The receiver operating characteristic (ROC) curve was used to evaluate the prediction of FPG-CV on adverse outcomes. Results: All patients were divided into four groups based on the quartile of FPG-CV. The proportion of FPG-SD and insulin injections differed among the groups (P<0.05). Among the outcomes, the highest incidence rate was 26.3% for large for gestational age (LGA), 8.7% for premature delivery. FPG-CV remains independently associated with low birth weight [odds ratio (OR) =1.086, P=0.007], preterm birth (OR =1.069, P=0.012), and preeclampsia (OR =1.180, P<0.001). FPG-CV can predict preeclampsia, with an area under the curve (AUC) of 0.725. Conclusions: Our results suggest that patients with gestational hyperglycemia should undergo routine FPG monitoring from diagnosis to delivery. Also, the impact of blood glucose fluctuations on adverse outcomes should be considered in the clinical treatment. The rational application of hypoglycemic treatment can stabilize blood glucose levels, however, the effects of different regimens on GV and outcomes should be studied further.

MUNIX repeatability evaluation method based on FastICA demixing.

To enhance the reproducibility of motor unit number index (MUNIX) for evaluating neurological disease progression, this paper proposes a negative entropy-based fast independent component analysis (FastICA) demixing method to assess MUNIX reproducibility in the presence of inter-channel mixing of electromyography (EMG) signals acquired by high-density electrodes. First, composite surface EMG (sEMG) signals were obtained using high-density surface electrodes. Second, the FastICA algorithm based on negative entropy was employed to determine the orthogonal projection matrix that minimizes the negative entropy of the projected signal and effectively separates mixed sEMG signals. Finally, the proposed experimental approach was validated by introducing an interrelationship criterion to quantify independence between adjacent channel EMG signals, measuring MUNIX repeatability using coefficient of variation (CV), and determining motor unit number and size through MUNIX. Results analysis shows that the inclusion of the full (128) channel sEMG information leads to a reduction in CV value by $1.5 \pm 0.1$ and a linear decline in CV value with an increase in the number of channels. The correlation between adjacent channels in participants decreases by $0.12 \pm 0.05$ as the number of channels gradually increases. The results demonstrate a significant reduction in the number of interrelationships between sEMG signals following negative entropy-based FastICA processing, compared to the mixed sEMG signals. Moreover, this decrease in interrelationships becomes more pronounced with an increasing number of channels. Additionally, the CV of MUNIX gradually decreases with an increase in the number of channels, thereby optimizing the issue of abnormal MUNIX repeatability patterns and further enhancing the reproducibility of MUNIX based on high-density surface EMG signals.

Analysis of spatiotemporal difference and driving factors of green total factor energy efficiency in RCEP members: insights from SBM-GML and Tobit models.

It is vital to determine the changing spatiotemporal patterns and driving factors of green total factor energy efficiency (GTFEE) in order to design scientific policies to promote energy efficiency in the Regional Comprehensive Economic Partnership (RCEP) region. From 2010 to 2019, the super-efficient SBM model and the global Malmquist-Luenberger index provide an appropriate framework for measuring the spatiotemporal evolution of GTFEE and the dynamics of energy productivity in RCEP countries. With the coefficient of variation and the Thiel index, an extensive view of the spatiotemporal variance in GTFEE is offered, taking regional heterogeneity into account. Furthermore, the Tobit model is introduced to investigate the factors influencing the GTFEE of RCEP members, which may address the restricted values of the dependent variable when compared to the least squares regression model. Findings suggest that (1) The GTFEE of RCEP members tends to be low and unevenly distributed spatially and temporally, with much room for improvement. (2) The energy productivity index fluctuates strongly, and the improvement primarily comes from technological progress. (3) The Non-ASEAN region possesses higher GTFEE than the ASEAN region, albeit regional variations are diminishing. (4) In terms of the major factors influencing the regional GTFEE, the non-ASEAN region looks to be distinct from the ASEAN region. The findings shed light on the trends and influencing factors of GTFEE in RCEP and serve as a resource for international energy cooperation and sustainable development.

Coefficient-of-variation-based channel selection with a new testing framework for MI-based BCI.

In the motor-imagery (MI) based brain computer interface (BCI), multi-channel electroencephalogram (EEG) is often used to ensure the complete capture of physiological phenomena. With the redundant information and noise, EEG signals cannot be easily converted into separable features through feature extraction algorithms. Channel selection algorithms are proposed to address the issue, in which the filtering technique is widely used with the advantages of low computational cost and strong practicability. In this study, we proposed several improved methods for filtering channel selection algorithm. Specifically, based on the coefficient of variation and inter-class distance, a novel channel classification method was designed, which divided channels into different categories based on their contribution to feature extraction process. Then a filtering channel selection algorithm was proposed according to the previous classification method. Moreover, a new testing framework for filtering channel selection algorithms was proposed, which can better reflect the generalization ability of the algorithm. Experimental results indicated that the proposed channel classification method is effective, and the proposed testing framework is better than the original one. Meanwhile, the proposed channel selection algorithm achieved the accuracy of 87.7% and 81.7% in two BCI competition datasets, respectively, which was superior to competing algorithms.

Quantitative hematoma heterogeneity associated with hematoma growth in patients with early intracerebral hemorrhage.

Background: Early hematoma growth is associated with poor functional outcomes in patients with intracerebral hemorrhage (ICH). We aimed to explore whether quantitative hematoma heterogeneity in non-contrast computed tomography (NCCT) can predict early hematoma growth. Methods: We used data from the Risk Stratification and Minimally Invasive Surgery in Acute Intracerebral Hemorrhage (Risa-MIS-ICH) trial. Our study included patients with ICH with a time to baseline NCCT <12 h and a follow-up CT duration <72 h. To get a Hounsfield unit histogram and the coefficient of variation (CV) of Hounsfield units (HUs), the hematoma was segmented by software using the auto-segmentation function. Quantitative hematoma heterogeneity is represented by the CV of hematoma HUs. Multivariate logistic regression was utilized to determine hematoma growth parameters. The discriminant score predictive value was assessed using the area under the ROC curve (AUC). The best cutoff was determined using ROC curves. Hematoma growth was defined as a follow-up CT hematoma volume increase of >6 mL or a hematoma volume increase of 33% compared with the baseline NCCT. Results: A total of 158 patients were enrolled in the study, of which 31 (19.6%) had hematoma growth. The multivariate logistic regression analysis revealed that time to initial baseline CT (P = 0.040, odds ratio [OR]: 0.824, 95 % confidence interval [CI]: 0.686-0.991), "heterogeneous" in the density category (P = 0.027, odds ratio [OR]: 5.950, 95 % confidence interval [CI]: 1.228-28.828), and CV of hematoma HUs (P = 0.018, OR: 1.301, 95 % CI: 1.047-1.617) were independent predictors of hematoma growth. By evaluating the receiver operating characteristic curve, the CV of hematoma HUs (AUC = 0.750) has a superior predictive value for hematoma growth than for heterogeneous density (AUC = 0.638). The CV of hematoma HUs had an 18% cutoff, with a specificity of 81.9 % and a sensitivity of 58.1 %. Conclusion: The CV of hematoma HUs can serve as a quantitative hematoma heterogeneity index that predicts hematoma growth in patients with early ICH independently.

Evaluating an external quality assurance program for semen analysis in China during 2009-2020.

INTRODUCTION: Semen analysis (SA) plays a key role in guiding treatments of male reproductive diseases and infertility due to male factors; however, it remains challenging to conduct an accurate SA due to lack of standardization, highly subjective assessments, and problems with automated procedures. Therefore, quality assurance (QA) and teaching courses are essential for making the laboratory results more consistent. MATERIALS AND METHODS: The external quality assurance (EQA) scheme was organized by national human sperm bank technology training bases in Guangdong province in China between 2009 and 2020. Until 2020, 124 laboratories from China participated in the EQA program. The EQA scheme per year has been organized involving two semen aliquots for sperm concentration, two video recordings for motility, and two smears for sperm morphology. All samples used in the EQA scheme were obtained from different healthy donors or patients. RESULTS: We estimated that the median coefficient of variation (CV) of sperm concentration, ignoring the method used, was 26.6%. Using a 100 µm deep counting chamber led to a decreasing CV of 13.6%. For sperm motility, the median CV of nonprogressive motility was high (50.8%), but the CV of progressive motility (13.2%), immotile sperm (14.3%), and total motility (11.8%) were acceptable. The morphology assessment revealed large variability (44.4%) irrespective of the classification criteria. DISCUSSION: The reduction of interlaboratory variability is still a challenge during SA in China. Therefore, it is critical to increase awareness of joining EQA schemes and establish standardized training centers to follow WHO-recommended procedures toward Chinese standards.

Optimized low-dose positron emission tomography/computed tomography schemes in pediatric tumor patients: a randomized clinical trial.

Background: It's clinically relevant to reduce the radiation dose to children while ensuring their positron emission tomography/computed tomography (PET/CT) image quality. The optimal protocol for whole-body PET/CT imaging in children (non-model) has been less studied. In this study, we investigated the optimal protocol for PET/CT imaging of pediatric oncology by analyzing the radiation dose and image quality in18F-fluoro-2-deoxy-D-glucose (18F-FDG) PET/CT imaging of children with oncology. Methods: One hundred children with tumors who underwent 18F-FDG PET/CT were included. CT grouping: randomly divided into 18 groups A-R according to the combination of three parameters: tube voltage (80/120 kV), automatic milliamp range (20-39/40-59/60-80 mA), and noise index (NI) (8/12/14). PET grouping: randomly divided into 9 groups a-i according to the combination of two parameters: the pharmaceuticals injection dose (0.08/0.12/0.15 mCi/kg) and time per bed (120/150/180 s). The effective radiation dose (ED) was calculated separately for each group and the image quality of CT and PET was evaluated subjectively using standard deviation (SD) and coefficient of variation (CV) objective evaluation and 5-point evaluation method, respectively. Results: Ninety-seven images in CT and 57 images in PET were included. The best quality of CT images was in group K (120 kV/40-59 mA/8); there are 9 groups had good image quality and lower dose length product (DLP) than group K (SD ±10), while the difference in DLP between groups was large. The Kruskal-Wallis (K-W) test showed that the difference in image quality between the 9 groups was not statistically significant. The best PET image quality was in group i [0.15 (mCi/kg)/180 s]; there are four groups had good image quality and lower EDPET than group i (CV ±3.5%), while the difference in EDPET between groups was large (4.4-6.5 mSv), and the K-W test showed that the difference in image quality between the four groups was not statistically significant (P>0.05), with the lowest EDPET being in the g group. Conclusions: The optimal protocols for CT scanning and PET imaging in this experiment were group H (80 kV/40-59 mA/14) and group g [0.08 (mCi/kg)/180 s], respectively.Trial Registration: Chinese Clinical Trial Registry ChiCTR2200061386.

Comparison of ADVIA Centaur ultra-sensitive and high-sensitive assays for troponin I in serum.

Cardiac troponin I (cTnI) is a standard biomarker for the diagnosis of acute myocardial infarction (AMI). While older, ultra-sensitive cTnI (us-cTnI) assays use the 99th percentile as the reference threshold, newer high-sensitive cTnI (hs-cTnI) assays use the limit of detection or functional sensitivity instead. However, little has been done to systematically compare these two methods. The present study also served as a validation of hs-cTnI in our laboratory. Here, we compared the results obtained from the blood serum obtained from 8810 patients using the us-cTnI and the hs-cTnI assays run in tandem on the ADVIA Centaur XP analyser. We found that in 2279 samples the concentration of cTnI measured with the ultra-sensitive method was below the detection limit, while with the high-sensitive method, only 540 were below the detection limit. We also compared results from these assays with the ultimate diagnosis of a subset of individuals. The analysis of the results below cut-off with the ultra-sensitive method showed that this method would not detect 96 cases related to heart disorder. Overall, the main finding of our research is that hs-cTnI is the preferable option and is able to be deployed effectively in the laboratory setting.

Variation in the "coefficient of variation": Rethinking the violation of the scalar property in time-duration judgments.

The coefficient of variation (CV), also known as relative standard deviation, has been used to measure the constancy of the Weber fraction, a key signature of efficient neural coding in time perception. It has long been debated whether or not duration judgments follow Weber's law, with arguments based on examinations of the CV. However, what has been largely ignored in this debate is that the observed CVs may be modulated by temporal context and decision uncertainty, thus questioning conclusions based on this measure. Here, we used a temporal reproduction paradigm to examine the variation of the CV with two types of temporal context: full-range mixed vs. sub-range blocked intervals, separately for intervals presented in the visual and auditory modalities. We found a strong contextual modulation of both interval-duration reproductions and the observed CVs. We then applied a two-stage Bayesian model to predict those variations. Without assuming a violation of the constancy of the Weber fraction, our model successfully predicted the central-tendency effect and the variation in the CV. Our findings and modeling results indicate that both the accuracy and precision of our timing behavior are highly dependent on the temporal context and decision uncertainty. And, critically, they advise caution with using variations of the CV to reject the constancy of the Weber fraction of duration estimation.

Glucose Time In Range, Time Above Range, and Time Below Range Depend on Mean or Median Glucose or HbA1c, Glucose Coefficient of Variation, and Shape of the Glucose Distribution.

Background: Examine the expected relationships between time in range (%TIR), time above range (%TAR), and time below range (%TBR) with median glucose (or %HbA1c) and %coefficient of variation (%CV) of glucose for various shapes of the glucose distribution. Methods: We considered several thresholds defining hypoglycemia and hyperglycemia and examined wide ranges of median glucose and %CV using three models for the glucose distribution: gaussian, log-gaussian, and a modified log-gaussian distribution. Results: There is a linear relationship between %TIR and median glucose for any specified %CV when median glucose is well removed from the threshold for hypoglycemia. %TIR reaches a peak when median glucose is close to 120 mg/dL and declines both at higher and lower median glucose values. There is a nearly linear relationship for %TAR and median glucose for a wider range of glucose (80-220 mg/dL). Risk of hypoglycemia is minimal when %CV is below 20%, but rises exponentially as %CV increases or as median glucose decreases. Similar results were obtained for a wide range of possible shapes of glucose distribution. These simulations are consistent with results from clinical studies. Conclusion: Both %TIR and %TAR are approximately linearly related to mean and median glucose (or %HbA1c). %TAR provides linearity over a wider range than %TIR. Risk of hypoglycemia (%TBR) is critically dependent on both glycemic variability (%CV) and mean or median glucose. These relationships support the use of %TIR, %TAR, and %TBR as metrics of quality of glycemic control for clinical, research, and regulatory purposes.

Evaluation of Different Estimation Methods for Accuracy and Precision in Biological Assay Validation.

Biological assays (bioassays) are procedures to estimate the potency of a substance by studying its effects on living organisms, tissues, and cells. Bioassays are essential tools for gaining insight into biologic systems and processes including, for example, the development of new drugs and monitoring environmental pollutants. Two of the most important parameters of bioassay performance are relative accuracy (bias) and precision. Although general strategies and formulas are provided in USP<1033>, a comprehensive understanding of the definitions of bias and precision remain elusive. Additionally, whether there is a beneficial use of data transformation in estimating intermediate precision remains unclear. Finally, there are various statistical estimation methods available that often pose a dilemma for the analyst who must choose the most appropriate method. To address these issues, we provide both a rigorous definition of bias and precision as well as three alternative methods for calculating relative standard deviation (RSD). All methods perform similarly when the RSD ≤10%. However, the USP estimates result in larger bias and root-mean-square error (RMSE) compared to the three proposed methods when the actual variation was large. Therefore, the USP method should not be used for routine analysis. For data with moderate skewness and deviation from normality, the estimates based on the original scale perform well. The original scale method is preferred, and the method based on log-transformation may be used for noticeably skewed data.LAY ABSTRACT: Biological assays, or bioassays, are essential in the development and manufacture of biopharmaceutical products for potency testing and quality monitoring. Two important parameters of assay performance are relative accuracy (bias) and precision. The definitions of bias and precision in USP 〈1033〉 are elusive and confusing. Another complicating issue is whether log-transformation should be used for calculating the intermediate precision. It is often challenging for analysts to pick the most appropriate estimation method. To address these issues, we give a rigorous definition of bias and precision and provide three alternative methods of calculating RSD. We demonstrate that the RSD formula in USP 〈1033〉 tends to have larger bias and root-mean-square error (RMSE) than the three proposed methods.

To Produce or to Survive: How Plastic Is Your Crop Stress Physiology?

Abiotic stress causes major crop losses and is considered a greater challenge than biotic stress. Comparisons of the number of published articles and patents regarding these different types of stresses, and the number of commercially released crops designed to tolerate different types of stresses, revealed a huge gap in the bench-to-field transfer rate of abiotic stress-tolerant crops, as compared to crops designed to tolerate biotic stress. These differences underscore the complexity of abiotic stress-response mechanisms. Here, we suggest that breeding programs favoring yield-related quantitative physiological traits (QPTs; e.g., photosynthesis rate or stomatal conductance) have canalized those QPTs at their highest levels. This has affected the sensitivity of those QPTs to changing environmental conditions and those traits have become less plastic. We also suggest that breeding pressure has had an asymmetric impact on different QPTs, depending on their sensitivity to environmental conditions and their interactions with other QPTs. We demonstrate this asymmetric impact on the regulation of whole-plant water balance, showing how plastic membrane water content, stomatal conductance and leaf hydraulic conductance interact to canalize whole-organ water content. We suggest that a QPT's plasticity is itself an important trait and that understanding this plasticity may help us to develop yield-optimized crops.

Designing a multiple dependent state sampling plan based on the coefficient of variation.

A multiple dependent state (MDS) sampling plan is developed based on the coefficient of variation of the quality characteristic which follows a normal distribution with unknown mean and variance. The optimal plan parameters of the proposed plan are solved by a nonlinear optimization model, which satisfies the given producer's risk and consumer's risk at the same time and minimizes the sample size required for inspection. The advantages of the proposed MDS sampling plan over the existing single sampling plan are discussed. Finally an example is given to illustrate the proposed plan.