Explore the vast range of titles available.

Enzootic pneumonia still causes major economic losses to the intensive pig production. Vaccination against its primary pathogen, , is carried out worldwide to control the disease and minimize clinical signs and performance losses. Nonetheless, the effects of both infection with, and vaccination against on the innate and adaptive immune responses remain largely unknown. Therefore, we conducted a study in which piglets were injected once with a commercial bacterin V1 or V2, or the adjuvant of V1 (A) to investigate their effect on local, innate and adaptive immune responses. Three weeks after vaccination, piglets were challenge infected with and euthanized four weeks later to assess vaccine efficacy macroscopic and microscopic evaluation of lung lesions. Blood and broncho-alveolar lavage fluid (BAL) samples were collected to measure antibody responses, cellular immunity, BAL cytokine levels and BAL DNA load as well as cytokine secretion by monocytes. After vaccination, proliferation of antigen-specific CD3 T cells and a higher percentage of TNF-α CD8 , and TNF-α and TNF-α IFN-γ CD4 CD8 T cells was seen in V1, while proliferation of or a significant increase in cytokine production by different T cell subsets could not be observed for animals from V2. Interestingly, LPS-stimulated blood monocytes from V1 and A secreted less IL-10 on D7. After challenge, higher levels of IgA, more IL-10 and less IL-1β was detected in BAL from V1, which was not observed in V2. Animals from A had significantly more IL-17A in BAL. The macroscopic lung lesion score and the DNA load at euthanasia was lower in V1, but the microscopic lung lesion score was lower in both vaccinated groups. In conclusion, these results indicate that the two commercial bacterins induced different local and adaptive immune responses, that the adjuvant alone can reduce anti-inflammatory innate immune responses, and that both vaccines had a different efficacy to reduce -like lung lesions and DNA load in the lung.

Digital PCR (dPCR) has been used in the field of virology since its inception. Technological innovations in microfluidics more than a decade ago caused a sharp increase in its use. There is an emerging consensus that dPCR now outperforms quantitative PCR (qPCR) in the basic parameters such as precision, sensitivity, accuracy, repeatability and resistance to inhibitors. These strengths have led to several current applications in quantification, mutation detection and environmental DNA and RNA samples. In high throughput scenarios, such as the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, the cost and throughput still significantly hampered the adaption of dPCR. There is much unexplored potential within the multiplexing capabilities of dPCR. This will allow simultaneous multi-target quantification and can also partially alleviate the throughput and cost drawback. In this review, we discuss the strengths and weaknesses of dPCR with a focus on virology applications and we discuss future applications. Finally, we discuss recent evolutions of the technology in the form of real-time dPCR and digital high-resolution melting.

Digital PCR (dPCR) has been used in the field of virology since its inception. Technological innovations in microfluidics more than a decade ago caused a sharp increase in its use. There is an emerging consensus that dPCR now outperforms quantitative PCR (qPCR) in the basic parameters such as precision, sensitivity, accuracy, repeatability and resistance to inhibitors. These strengths have led to several current applications in quantification, mutation detection and environmental DNA and RNA samples. In high throughput scenarios, such as the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, the cost and throughput still significantly hampered the adaption of dPCR. There is much unexplored potential within the multiplexing capabilities of dPCR. This will allow simultaneous multi-target quantification and can also partially alleviate the throughput and cost drawback. In this review, we discuss the strengths and weaknesses of dPCR with a focus on virology applications and we discuss future applications. Finally, we discuss recent evolutions of the technology in the form of real-time dPCR and digital high-resolution melting.

Digital polymerase chain reaction (dPCR) is a state-of-the-art targeted quantification method of nucleic acids. The technology is based on massive partitioning of a reaction mixture into individual PCR reactions. The resulting partition-level end-point fluorescence intensities are used to classify partitions as positive or negative, i.e. containing or not containing the target nucleic acid(s). Many automatic dPCR partition classification methods have been proposed, but they are limited to the analysis of single- or dual-color dPCR data. While general-purpose or flow cytometry clustering methods can be directly applied to multicolor dPCR data, these methods do not exploit the approximate prior knowledge on cluster center locations available in dPCR data. We present Polytect, a method that relies on crude cluster results from flowPeaks, previously shown to offer good partition classification performance, and subsequently refines flowPeaks’ results by automatic cluster merging and cluster labeling, exploiting the prior knowledge on cluster center locations. Comparative analyses with established methods such as flowPeaks, dpcp, and ddPCRclust reveal that Polytect often surpasses established methods, both on empirical and simulated data. Polytect manages to merge excess clusters, while also successfully identifying empty clusters when fewer than the maximally observable number of clusters are present. On par with recent developments in instruments, Polytect extends beyond two-color data. The method is available as an R package and R Shiny app (https://digpcr.shinyapps.io/Polytect/).

Digital Polymerase chain reaction (dPCR) enables precise and absolute quantification of nucleic acids by partitioning samples into thousands of individual PCR micro-reactions. While it minimizes the need for standard curves and enhances reproducibility compared to qPCR, thorough assay validation remains crucial. We introduce PCR-ValiPal, a user-friendly web application that standardizes dPCR assay validation steps and streamlines calculations of limit of blank (LOB), limit of detection (LOD), limit of quantification (LOQ), precision, trueness, and linearity in accordance with International Organization for Standardization (ISO) 20395:2019. To demonstrate PCR-ValiPal’s capabilities and the value of method-specific optimization, we use it to validate a novel three-color PCR assay for Bovine Papillomavirus (BPV) types 1 and 2, comparing four platforms: Naica (droplet dPCR), QIAcuity (microwell dPCR), LOAA (real-time dPCR), and CFX96 (qPCR). Using synthetic standards, we assess the platforms’ performance under identical assay conditions. Naica and QIAcuity showed lower LOB and LOQ values, along with minimal bias for BPV-1, while LOAA demonstrated stable but negative bias. Although qPCR exhibited the highest sensitivity for BPV-2, it was less sensitive at low concentrations for BPV-1. These results underscore the value of method-specific optimization and the usefulness of PCR-ValiPal.

Digital PCR (dPCR) is a highly accurate and precise technique for the quantification of target nucleic acid(s) in a biological sample. This digital quantification relies on the binomial or Poisson distribution to estimate the amount of target molecules based on positive and negative partitions. However, the implementation of these distributions require adherence to underlying assumptions that are often neglected, leading to a suboptimal (too optimistic) variance estimation of the target concentration, especially when considering the multiple sources of variation in experimental dPCR setups. Moreover, these parametric methods cannot be easily used for downstream statistical inference when more advanced analysis are required, such as for copy number variation. We evaluated the performance of three new statistical methods (BootsVar, NonPVar, BinomVar) in both simulations and real-life datasets for target and variance estimation in dPCR setups while taking into account a combination of commonly observed sources of experimental variability that can interfere with the underlying assumptions of the current parametric methods. The results demonstrate the capability of the new methods for variance estimation and present a more accurate reflection of the true variability over the classical binomial approach. In addition, these statistical methods are flexible and generic in the way that they work well for the variance estimation of non-linear statistics that work with ratios (e.g. CNV) and for multiplex dPCR setups. In this study, we provide guidelines when to use the binomial-assumption based methods and when the non-parametric one is better to achieve more accurate variance estimates.

There is a pressing need for accessible biomarkers with high diagnostic accuracy for Alzheimer's disease (AD) diagnosis to facilitate widespread screening, particularly in underserved groups. Saliva is an emerging specimen for measuring AD biomarkers, with distinct contexts of use that could complement blood and cerebrospinal fluid and detect various analytes. An interdisciplinary, international group of AD and related dementias (ADRD) researchers convened and performed a narrative review of published studies on salivary AD biomarkers. We critically appraised the current state of the literature, examining both consistencies and discrepancies in existing pre‐analytical variables and methodologies. We discussed how various pre‐analytical variables could influence the detection and quantification of salivary biomarkers, showed technologies available to standardize collection procedures, and proposed a standardized pre‐analytical protocol to guide future studies on salivary AD biomarker examinations. We identified potential contexts of use, gaps, and priorities and proposed future research directions. Highlights Given its non‐invasive nature, wider accessibility, and cultural acceptability, particularly in low‐resourced settings, saliva is a biofluid complementary to blood and CSF. Current salivary AD biomarker studies do not control for many confounding pre‐analytical variables during the sampling process, potentially leading to inaccurate salivary biomarker readings and conclusions, contributing to conflicting findings. Reviewing the current literature, including the consistencies and non‐consistencies observed in the existing parameters and methodologies, discussing how they can affect salivary AD biomarker detection and quantification. Proposing a standardized salivary pre‐analytical protocol, identifying the gaps and prioritizations needed to move this area forward, proposing future directions and potential contexts of use.