Placental weight percentile curves in a Danish population

INTRODUCTION

The role of the placenta is to transport oxygen and nutrients to the fetus, and a well-functioning placenta is vital to fetal health. Our aim was to develop placental weight percentile curves adjusted by gestational age, and stratified by major maternal comorbidities.

MATERIAL AND METHODS

The study was a population study in a Danish cohort. Data was drawn from The Medical Birth Register and the National Patient Register. We included singleton births with a gestational age of 22 + 0 to 42 + 6 weeks. We excluded multiple pregnancies, stillbirths and retained placentas. A total of 611 418 placentas were included. Percentile line graphs were created in groups of all placentas, hypertensive disorders and diabetic disorders.

RESULTS

Tables and figures are presented for placental weight percentile curves according to gestational age for all placentas, hypertensive disorders and diabetic disorders, respectively. Placental weight was generally higher in the diabetic placentas, and lower in the hypertensive placentas.

CONCLUSIONS

These percentile curves may serve as a reference for other populations, and may be useful for other studies investigating the role of the placenta in relation to pregnancy outcomes, and health in later life.

Introduction to the Use of Linear and Nonlinear Regression Analysis in Quantitative Biological Assays

Biological assays are essential tools in biomedical and pharmaceutical research. In simplest terms, such an assay is an analytical method used to measure or predict a response in a biological system in the presence of a given stimulus (e.g., drug). The inherent complexity involved in evaluating a biological system requires the use of rigorous and appropriate tools for data analysis. Linear and nonlinear regression models represent critically important statistical analyses used to define the relationships between variables of interest in biological systems. Recent challenges relating to the reproducibility of published data suggest the absence of standardized and routine use of statistics to support experimental results across a wide range of scientific disciplines. The current situation warrants an introductory review of basic regression concepts using current, practical examples, along with references to in-depth resources. The goal is to provide the necessary information to help standardize the analysis of biological assays in academic research and drug discovery and development, elevating their utility and increasing data transparency and reproducibility. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC.

Sources of variance in the results of a commercial bovine immunoglobulin G radial immunodiffusion assay

Radial immunodiffusion (RID) is used to quantify IgG concentration in neonatal beef or dairy calf serum; variability has been noted that may affect the precision and accuracy of assay results. We determined the source, range, and homogeneity of variance in the results of a commercial bovine IgG RID assay (Triple J Farm). To estimate the variance in the precipitin ring diameter, we used 6 sera, measured 28 times across 8 plates and 4 lots, and 3 standards with known IgG concentrations, measured 75 times across 69 plates and 5 lots. The source of diameter variance was determined using variance partition coefficients for lot, plate, and repetition. We used 11 different methods to generate standard curves to convert RID precipitin ring diameters to IgG concentrations. The Levene test of homogeneity of variance (α = 0.1) was used to evaluate the equality of variance between the standards or serum precipitin ring diameters and calculated IgG concentrations. Lot and plate contributed minimally to the diameter variance. Precipitin ring diameters had equal variance. Calculated IgG concentrations for serum not requiring dilution had equal variance. A linear equation from aggregated standards, performed within the same day, had greater accuracy for the calculated IgG concentrations of the standards compared to other equation methods. Regardless of standard curve methodology or IgG concentration, variability inherent to the assay limits its clinical usefulness.

Variability in RT-qPCR assay parameters indicates unreliable SARS-CoV-2 RNA quantification for wastewater surveillance

Due to the coronavirus disease 2019 (COVID-19) pandemic, wastewater surveillance has become an important tool for monitoring the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) within communities. In particular, reverse transcription-quantitative PCR (RT-qPCR) has been used to generate large datasets aimed at detecting and quantifying SARS-CoV-2 RNA in wastewater. Although RT-qPCR is rapid and sensitive, there is no standard method yet, there are no certified quantification standards, and experiments are conducted using different assays, reagents, instruments, and data analysis protocols. These variations can induce errors in quantitative data reports, thereby potentially misleading interpretations, and conclusions. We review the SARS-CoV-2 wastewater surveillance literature focusing on variability of RT-qPCR data as revealed by inconsistent standard curves and associated parameters. We find that variation in these parameters and deviations from best practices, as described in the Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines suggest a frequent lack of reproducibility and reliability in quantitative measurements of SARS-CoV-2 RNA in wastewater.

Variability in RT-qPCR assay parameters indicates unreliable SARS-CoV-2 RNA quantification for wastewater surveillance

Due to the coronavirus disease 2019 (COVID-19) pandemic, wastewater surveillance has become an important tool for monitoring the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) within communities. In particular, reverse transcription-quantitative PCR (RT-qPCR) has been used to generate large datasets aimed at detecting and quantifying SARS-CoV-2 RNA in wastewater. Although RT-qPCR is rapid and sensitive, there is no standard method yet, there are no certified quantification standards, and experiments are conducted using different assays, reagents, instruments, and data analysis protocols. These variations can induce errors in quantitative data reports, thereby potentially misleading interpretations, and conclusions. We review the SARS-CoV-2 wastewater surveillance literature focusing on variability of RT-qPCR data as revealed by inconsistent standard curves and associated parameters. We find that variation in these parameters and deviations from best practices, as described in the Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines suggest a frequent lack of reproducibility and reliability in quantitative measurements of SARS-CoV-2 RNA in wastewater.

Detection and quantification of hepatitis E virus in the absence of IgG and IgM anti-HEV in HIV-positive patients

AIMS

To improve RT-qPCR with an internal control and a synthetic standard curve to detect HEV in HIV co-infected patients.

METHODS AND RESULTS

A single-stranded RNA (ssRNA) and a double-stranded DNA (dsDNA) synthetic curve were designed, compared to the international reference panel for HEV genotypes, and tested to quantify and detect a reference panel for HEV genotypes. The detection limit of the RNA synthetic curve (50 copies per ml) was better than the DNA synthetic curve (100 copies per ml) and the WHO standard curve (250 copies per ml). Then, 280 serum samples from HIV-positive patients were tested for HEV RNA, which was detected in 3·6% of serum samples. The viral load ranged from 2 × 10² copies per ml to 4·78 × 10⁸ copies per ml. HEV IgM/IgG antibodies were not detected in the RNA-positive patients. Sequencing analysis of HEV showed that the virus belongs to genotype 3 (HEV GT3).

CONCLUSIONS

Real-time PCR was a useful tool to estimate co-infection with HEV/HIV, even in patients with low viral loads and undetectable anti-HEV IgG and IgM antibodies.

SIGNIFICANCE AND IMPACT OF THE STUDY

Hepatitis E virus genotype 3 (HEV GT3) has been associated with silent chronic hepatitis and cirrhosis in HIV-positive subjects worldwide, but there is a lack of data on this co-infection in Brazil.

Standard Curves Are Necessary to Determine Pharmacological Properties for Ligands in Functional Assays Using Competition Binding Technologies

Homogeneous functional assays that utilize competition binding technology are widely used for determining pharmacological properties such as intrinsic activity and potency. One example is time-resolved fluorescence resonance energy transfer (TR-FRET) 3',5'-cyclic adenosine monophosphate (cAMP) assays, where labeled cAMP (tracer) and a labeled anti-cAMP antibody bind together to produce a TR-FRET signal when the two constituents are proximal to each other. This signal is disrupted when unlabeled and cellularly generated cAMP competes with the tracer cAMP for binding to the labeled antibody. It is important that the resulting assay signal, usually expressed as a TR-FRET ratio, be transformed to cAMP concentration using a cAMP standard curve. However, examples are still generated in the literature wherein investigators have used the ratiometric signal (not transformed using a standard curve) to determine values for intrinsic activity and potency of ligands. Untransformed raw data often produce reasonable looking sigmoidal concentration response curves, perhaps tempting investigators to use the raw data instead of the transformed data for applying pharmacological models. In this article, we describe the correct procedure for determining the potency and intrinsic activity of ligands that result in changes in cAMP levels using a lysate dilution assay of GLP-1 (7-36)-mediated TR-FRET cAMP accumulation and simulated data. We also highlight how the inappropriate use of raw signal data can dramatically affect interpretation of intrinsic activity and potency of ligands, and how this can adversely affect drug discovery programs. These findings apply not only to cAMP functional assays but also to other functional cellular signaling assays that utilize competition binding technologies.

Evaluation of cockerel spermatozoa viability and motility by a novel enzyme based cell viability assay

1. The results of spermatozoa assessment by the WST-8 (2-[2-methoxy-4-nitrophenyl]-3-[4-nitrophenyl]-5-[2,4-disulfophenyl]-2H-tetrazolium, monosodium salt) assay, flow cytometry (FC) or computer-assisted sperm analysis (CASA) were compared. 2. Different live/killed ratios of cockerel semen were serially diluted to 120, 60, and 30 × 10⁶ cells/ml, and each sample was analysed by (1) WST-8 assay at 0, 10, 20, 30, 40, 50, 60 min, (2) viability with FC, and (3) motility with CASA. 3. The WST-8 reduction rate was closely correlated with spermatozoa viability and motility. The optimal semen concentration for the WST-8 assay was 120 × 10⁶ cells/ml, and the standard curves for spermatozoa viability and motility predictions, respectively, were y_viability60 = 162.8x + 104.96 (R² = 0.9594) after 60 min of incubation and y_motility40 = 225.09x + 96.299 (R² = 0.8475) after 40 min of incubation. 4. It was concluded that the WST-8 assay is useful for the practical evaluation of cockerel spermatozoa viability and motility. Compared to FC and CASA, the WST-8 assay does not require expensive and complex instrumentation in the lab. Furthermore, one well of the WST-8 reaction can be used to predict spermatozoa viability and motility at the same time, which all lead it to be efficient and economical for semen quality assessment.

ExSTA: External Standard Addition Method for Accurate High-Throughput Quantitation in Targeted Proteomics Experiments

PURPOSE

Targeted proteomics using MRM with stable-isotope-labeled internal-standard (SIS) peptides is the current method of choice for protein quantitation in complex biological matrices. Better quantitation can be achieved with the internal standard-addition method, where successive increments of synthesized natural form (NAT) of the endogenous analyte are added to each sample, a response curve is generated, and the endogenous concentration is determined at the x-intercept. Internal NAT-addition, however, requires multiple analyses of each sample, resulting in increased sample consumption and analysis time.

EXPERIMENTAL DESIGN

To compare the following three methods, an MRM assay for 34 high-to-moderate abundance human plasma proteins is used: classical internal SIS-addition, internal NAT-addition, and external NAT-addition-generated in buffer using NAT and SIS peptides. Using endogenous-free chicken plasma, the accuracy is also evaluated.

RESULTS

The internal NAT-addition outperforms the other two in precision and accuracy. However, the curves derived by internal vs. external NAT-addition differ by only ≈3.8% in slope, providing comparable accuracies and precision with good CV values.

CONCLUSIONS AND CLINICAL RELEVANCE

While the internal NAT-addition method may be "ideal", this new external NAT-addition can be used to determine the concentration of high-to-moderate abundance endogenous plasma proteins, providing a robust and cost-effective alternative for clinical analyses or other high-throughput applications.

Handheld real-time PCR device

Here we report one of the smallest real-time polymerase chain reaction (PCR) systems to date with an approximate size of 100 mm × 60 mm × 33 mm. The system is an autonomous unit requiring an external 12 V power supply. Four simultaneous reactions are performed in the form of virtual reaction chambers (VRCs) where a ≈200 nL sample is covered with mineral oil and placed on a glass cover slip. Fast, 40 cycle amplification of an amplicon from the H7N9 gene was used to demonstrate the PCR performance. The standard curve slope was -3.02 ± 0.16 cycles at threshold per decade (mean ± standard deviation) corresponding to an amplification efficiency of 0.91 ± 0.05 per cycle (mean ± standard deviation). The PCR device was capable of detecting a single deoxyribonucleic acid (DNA) copy. These results further suggest that our handheld PCR device may have broad, technologically-relevant applications extending to rapid detection of infectious diseases in small clinics.

Novel isotopic N,N-dimethyl leucine (iDiLeu) reagents enable absolute quantification of peptides and proteins using a standard curve approach

Absolute quantification of protein targets using liquid chromatography-mass spectrometry (LC-MS) is a key component of candidate biomarker validation. One popular method combines multiple reaction monitoring (MRM) using a triple quadrupole instrument with stable isotope-labeled standards (SIS) for absolute quantification (AQUA). LC-MRM AQUA assays are sensitive and specific, but they are also expensive because of the cost of synthesizing stable isotope peptide standards. While the chemical modification approach using mass differential tags for relative and absolute quantification (mTRAQ) represents a more economical approach when quantifying large numbers of peptides, these reagents are costly and still suffer from lower throughput because only two concentration values per peptide can be obtained in a single LC-MS run. Here, we have developed and applied a set of five novel mass difference reagents, isotopic N,N-dimethyl leucine (iDiLeu). These labels contain an amine reactive group, triazine ester, are cost effective because of their synthetic simplicity, and have increased throughput compared with previous LC-MS quantification methods by allowing construction of a four-point standard curve in one run. iDiLeu-labeled peptides show remarkably similar retention time shifts, slightly lower energy thresholds for higher-energy collisional dissociation (HCD) fragmentation, and high quantification accuracy for trypsin-digested protein samples (median errors <15%). By spiking in an iDiLeu-labeled neuropeptide, allatostatin, into mouse urine matrix, two quantification methods are validated. The first uses one labeled peptide as an internal standard to normalize labeled peptide peak areas across runs (<19% error), whereas the second enables standard curve creation and analyte quantification in one run (<8% error).