Safety of Combined Treatment With Monoclonal Antibodies and Viscum album L Preparations

Combination strategies involving chemotherapy and monoclonal antibodies (mAb) are commonly used in attempts to produce better clinical outcomes. This practice has led to new and ongoing toxicities that may lead to reductions in dose or noncompliance, limiting the effectiveness of treatment. Viscum album L (VA) preparations are widely used in Europe as additive therapy and have been associated with reduced chemotherapy-related adverse reactions and increased health-related quality of life. Concomitant VA therapy might also reduce toxicity related to mAb. This retrospective study investigated the safety of combined treatment with VA and mAb in cancer patients. A total of 43 patients had combined therapy (474 exposures); 12 had VA without mAb (129 exposures), and 8 had mAb without VA (68 exposures). Most patients (89.3%) received concomitant chemotherapy or supportive therapies. A total of 34 patients (60.7%) experienced 142 adverse events (AEs). Leucopenia (14.1% of all events), acneiform rash (8.5%), and stomatitis (6.3%) occurred most frequently. Longitudinal logistic regression analysis suggested a nearly 5 times higher odds of experiencing an AE following treatment with mAb compared with mAb plus VA (95% CI = 1.53-16.14). Our results, together with theoretical consideration of potential botanical-drug interactions, suggest that combined treatment with VA and mAb is safe

An efficient and robust laboratory workflow and tetrapod database for larger scale environmental DNA studies

BACKGROUND: The use of environmental DNA for species detection via metabarcoding is growing rapidly. We present a co-designed lab workflow and bioinformatic pipeline to mitigate the 2 most important risks of environmental DNA use: sample contamination and taxonomic misassignment. These risks arise from the need for polymerase chain reaction (PCR) amplification to detect the trace amounts of DNA combined with the necessity of using short target regions due to DNA degradation. FINDINGS: Our high-throughput workflow minimizes these risks via a 4-step strategy: (i) technical replication with 2 PCR replicates and 2 extraction replicates; (ii) using multi-markers (12S,16S,CytB); (iii) a "twin-tagging," 2-step PCR protocol; and (iv) use of the probabilistic taxonomic assignment method PROTAX, which can account for incomplete reference databases. Because annotation errors in the reference sequences can result in taxonomic misassignment, we supply a protocol for curating sequence datasets. For some taxonomic groups and some markers, curation resulted in >50% of sequences being deleted from public reference databases, owing to (i) limited overlap between our target amplicon and reference sequences, (ii) mislabelling of reference sequences, and (iii) redundancy. Finally, we provide a bioinformatic pipeline to process amplicons and conduct PROTAX assignment and tested it on an invertebrate-derived DNA dataset from 1,532 leeches from Sabah, Malaysia. Twin-tagging allowed us to detect and exclude sequences with non-matching tags. The smallest DNA fragment (16S) amplified most frequently for all samples but was less powerful for discriminating at species rank. Using a stringent and lax acceptance criterion we found 162 (stringent) and 190 (lax) vertebrate detections of 95 (stringent) and 109 (lax) leech samples. CONCLUSIONS: Our metabarcoding workflow should help research groups increase the robustness of their results and therefore facilitate wider use of environmental and invertebrate-derived DNA, which is turning into a valuable source of ecological and conservation information on tetrapods

Validation of internal reference genes for quantitative real-time PCR in a non-model organism, the yellow-necked mouse, Apodemus flavicollis

<p>Abstract</p> <p>Background</p> <p>Reference genes are used as internal standards to normalize mRNA abundance in quantitative real-time PCR and thereby allow a direct comparison between samples. So far most of these expression studies used human or classical laboratory model species whereas studies on non-model organism under in-situ conditions are quite rare. However, only studies in free-ranging populations can reveal the effects of natural selection on the expression levels of functional important genes. In order to test the feasibility of gene expression studies in wildlife samples we transferred and validated potential reference genes that were developed for lab mice (<it>Mus musculus</it>) to samples of wild yellow-necked mice, <it>Apodemus flavicollis</it>. The stability and suitability of eight potential reference genes was accessed by the programs BestKeeper, NormFinder and geNorm.</p> <p>Findings</p> <p>Although the three programs used different algorithms the ranking order of reference genes was significantly concordant and geNorm differed in only one, NormFinder in two positions compared to BestKeeper. The genes ordered by their mean rank from the most to the least stable gene were: <it>Rps18</it>, <it>Sdha</it>, <it>Canx</it>, <it>Actg1</it>, <it>Pgk1</it>, <it>Ubc</it>, <it>Rpl13a </it>and <it>Actb</it>. Analyses of the normalization factor revealed best results when the five most stable genes were included for normalization.</p> <p>Discussion</p> <p>We established a SYBR green qPCR assay for liver samples of wild <it>A. flavicollis </it>and conclude that five genes should be used for appropriate normalization. Our study provides the basis to investigate differential expression of genes under selection under natural selection conditions in liver samples of <it>A. flavicollis</it>. This approach might also be applicable to other non-model organisms.</p

Rezension zu Christof Wingertszahn (Hg.): Eroberung, Erfindung, Philosophie und Poesie. ‚Natur‘ in der Romantik

Anna Axtner-Borsutzky rezensiert den von Christof Wingertszahn herausgegebenen Sammelband „Eroberung, Erfindung, Philosophie und Poesie. ‚Natur‘ in der Romantik'"

SELECTIVE MEASUREMENT OF α SMOOTH MUSCLE ACTIN: WHY β-ACTIN CAN NOT BE USED AS A HOUSEKEEPING GENE WHEN TISSUE FIBROSIS OCCURS

Abstract Background Prevalence of fibroproliferative diseases, including chronic kidney disease is rapidly increasing and has become a major public health problem worldwide. Fibroproliferative diseases are characterized by increased expression of α smooth muscle actin (α-SMA) that belongs to the family of the six conserved actin isoforms showing high degree homology. The aim of the present study was to develop real-time PCRs that clearly discriminate α-SMA and ß-actin from other actin isoforms. Results Real-time PCRs using self-designed mouse, human and rat specific α-SMA or ß-actin primer pairs resulted in the specific amplification of the artificial DNA templates corresponding to mouse, human or rat α-SMA or ß-actin, however ß-actin showed cross-reaction with the housekeeping γ-cyto-actin. We have shown that the use of improperly designed literary primer pairs significantly affects the results of PCRs measuring mRNA expression of α-SMA or ß-actin in the kidney of mice underwent UUO. Conclusion We developed a set of carefully designed primer pairs and PCR conditions to selectively determine the expression of mouse, human or rat α-SMA and ß-actin isoforms. We demonstrated the importance of primer specificity in experiments where the results are normalized to the expression of ß-actin especially when fibrosis and thus increased expression of α-SMA is occur

imageseg: An R package for deep learning-based image segmentation

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2022 The Authors. Methods in Ecology and Evolution published by John Wiley & Sons Ltd on behalf of British Ecological SocietyConvolutional neural networks (CNNs) and deep learning are powerful and robust tools for ecological applications and are particularly suited for image data. Image segmentation (the classification of all pixels in images) is one such application and can, for example, be used to assess forest structural metrics. While CNN-based image segmentation methods for such applications have been suggested, widespread adoption in ecological research has been slow, likely due to technical difficulties in implementation of CNNs and lack of toolboxes for ecologists. Here, we present R package imageseg which implements a CNN-based workflow for general purpose image segmentation using the U-Net and U-Net++ architectures in R. The workflow covers data (pre)processing, model training and predictions. We illustrate the utility of the package with image recognition models for two forest structural metrics: tree canopy density and understorey vegetation density. We trained the models using large and diverse training datasets from a variety of forest types and biomes, consisting of 2877 canopy images (both canopy cover and hemispherical canopy closure photographs) and 1285 understorey vegetation images. Overall segmentation accuracy of the models was high with a Dice score of 0.91 for the canopy model and 0.89 for the understorey vegetation model (assessed with 821 and 367 images respectively). The image segmentation models performed significantly better than commonly used thresholding methods and generalized well to data from study areas not included in training. This indicates robustness to variation in input images and good generalization strength across forest types and biomes. The package and its workflow allow simple yet powerful assessments of forest structural metrics using pretrained models. Furthermore, the package facilitates custom image segmentation with single or multiple classes and based on colour or grayscale images, for example, for applications in cell biology or for medical images. Our package is free, open source and available from CRAN. It will enable easier and faster implementation of deep learning-based image segmentation within R for ecological applications and beyond.publishedVersio

Selection of reference genes for normalization of quantitative real-time PCR in organ culture of the rat and rabbit intervertebral disc

<p>Abstract</p> <p>Background</p> <p>The accuracy of quantitative real-time RT-PCR (qRT-PCR) is often influenced by experimental artifacts, resulting in erroneous expression profiles of target genes. The practice of employing normalization using a reference gene significantly improves reliability and its applicability to molecular biology. However, selection of an ideal reference gene(s) is of critical importance to discern meaningful results. The aim of this study was to evaluate the stability of seven potential reference genes (Actb, GAPDH, 18S rRNA, CycA, Hprt1, Ywhaz, and Pgk1) and identify most stable gene(s) for application in tissue culture research using the rat and rabbit intervertebral disc (IVD).</p> <p>Findings</p> <p><it>In vitro</it>, four genes (Hprt1, CycA, GAPDH, and 18S rRNA) in rat IVD tissue and five genes (CycA, Hprt1, Actb, Pgk1, and Ywhaz) in rabbit IVD tissue were determined as most stable for up to 14 days in culture. Pair-wise variation analysis indicated that combination of Hprt1 and CycA in rat and the combination of Hprt1, CycA, and Actb in rabbit may most stable reference gene candidates for IVD tissue culture.</p> <p>Conclusions</p> <p>Our results indicate that Hprt1 and CycA are the most stable reference gene candidates for rat and rabbit IVD culture studies. In rabbit IVD, Actb could be an additional gene employed in conjunction with Hprt1 and CycA. Selection of optimal reference gene candidate(s) should be a pertinent exercise before employment of PCR outcome measures for biomedical research.</p

Impact of historical founder effects and a recent bottleneck on MHC variability in Commander Arctic foxes (Vulpes lagopus)

Populations of Arctic foxes (Vulpes lagopus) have been isolated on two of the Commander Islands (Bering and Mednyi) from the circumpolar distributed mainland population since the Pleistocene. In 1970–1980, an epizootic outbreak of mange caused a severe population decline on Mednyi Island. Genes of the major histocompatibility complex (MHC) play a primary role in infectious disease resistance. The main objectives of our study were to compare contemporary variation of MHC class II in mainland and island Arctic foxes, and to document the effects of the isolation and the recent bottleneck on MHC polymorphism by analyzing samples from historical and contemporary Arctic foxes. In 184 individuals, we found 25 unique MHC class II DRB and DQB alleles, and identified evidence of balancing selection maintaining allelic lineages over time at both loci. Twenty different MHC alleles were observed in mainland foxes and eight in Bering Island foxes. The historical Mednyi population contained five alleles and all contemporary individuals were monomorphic at both DRB and DQB. Our data indicate that despite positive and diversifying selection leading to elevated rates of amino acid replacement in functionally important antigen-binding sites, below a certain population size, balancing selection may not be strong enough to maintain genetic diversity in functionally important genes. This may have important fitness consequences and might explain the high pathogen susceptibility in some island populations. This is the first study that compares MHC diversity before and after a bottleneck in a wild canid population using DNA from museum samples

Insights into the Complex Associations Between MHC Class II DRB Polymorphism and Multiple Gastrointestinal Parasite Infestations in the Striped Mouse

Differences in host susceptibility to different parasite types are largely based on the degree of matching between immune genes and parasite antigens. Specifically the variable genes of the major histocompatibility complex (MHC) play a major role in the defence of parasites. However, underlying genetic mechanisms in wild populations are still not well understood because there is a lack of studies which deal with multiple parasite infections and their competition within. To gain insights into these complex associations, we implemented the full record of gastrointestinal nematodes from 439 genotyped individuals of the striped mouse, Rhabdomys pumilio. We used two different multivariate approaches to test for associations between MHC class II DRB genotype and multiple nematodes with regard to the main pathogen-driven selection hypotheses maintaining MHC diversity and parasite species-specific co-evolutionary effects. The former includes investigations of a ‘heterozygote advantage’, or its specific form a ‘divergent-allele advantage’ caused by highly dissimilar alleles as well as possible effects of specific MHC-alleles selected by a ‘rare allele advantage’ ( = negative ‘frequency-dependent selection’). A combination of generalized linear mixed models (GLMMs) and co-inertia (COIA) analyses made it possible to consider multiple parasite species despite the risk of type I errors on the population and on the individual level. We could not find any evidence for a ‘heterozygote’ advantage but support for ‘divergent-allele’ advantage and infection intensity. In addition, both approaches demonstrated high concordance of positive as well as negative associations between specific MHC alleles and certain parasite species. Furthermore, certain MHC alleles were associated with more than one parasite species, suggesting a many-to-many gene-parasite co-evolution. The most frequent allele Rhpu-DRB*38 revealed a pleiotropic effect, involving three nematode species. Our study demonstrates the co-existence of specialist and generalist MHC alleles in terms of parasite detection which may be an important feature in the maintenance of MHC polymorphism