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Machine learning techniques are excellent to analyze expression data from single cells. These techniques impact all fields ranging from cell annotation and clustering to signature identification. The presented framework evaluates gene selection sets how far they optimally separate defined phenotypes or cell groups. This innovation overcomes the present limitation to objectively and correctly identify a small gene set of high information content regarding separating phenotypes for which corresponding code scripts are provided. The small but meaningful subset of the original genes (or feature space) facilitates human interpretability of the differences of the phenotypes including those found by machine learning results and may even turn correlations between genes and phenotypes into a causal explanation. For the feature selection task, the principal feature analysis is utilized which reduces redundant information while selecting genes that carry the information for separating the phenotypes. In this context, the presented framework shows explainability of unsupervised learning as it reveals cell-type specific signatures. Apart from a Seurat preprocessing tool and the PFA script, the pipeline uses mutual information to balance accuracy and size of the gene set if desired. A validation part to evaluate the gene selection for their information content regarding the separation of the phenotypes is provided as well, binary and multiclass classification of 3 or 4 groups are studied. Results from different single-cell data are presented. In each, only about ten out of more than 30000 genes are identified as carrying the relevant information. The code is provided in a GitHub repository at https://github.com/AC-PHD/Seurat_PFA_pipeline.
CRISPR/Cas9 gene editing has revolutionised loss-of-function experiments in Leishmania, the causative agent of leishmaniasis. As Leishmania lack a functional non-homologous DNA end joining pathway however, obtaining null mutants typically requires additional donor DNA, selection of drug resistance-associated edits or time-consuming isolation of clones. Genome-wide loss-of-function screens across different conditions and across multiple Leishmania species are therefore unfeasible at present. Here, we report a CRISPR/Cas9 cytosine base editor (CBE) toolbox that overcomes these limitations. We employed CBEs in Leishmania to introduce STOP codons by converting cytosine into thymine and created http://www.leishbaseedit.net/ for CBE primer design in kinetoplastids. Through reporter assays and by targeting single- and multi-copy genes in L. mexicana, L. major, L. donovani, and L. infantum, we demonstrate how this tool can efficiently generate functional null mutants by expressing just one single-guide RNA, reaching up to 100% editing rate in non-clonal populations. We then generated a Leishmania-optimised CBE and successfully targeted an essential gene in a plasmid library delivered loss-of-function screen in L. mexicana. Since our method does not require DNA double-strand breaks, homologous recombination, donor DNA, or isolation of clones, we believe that this enables for the first time functional genetic screens in Leishmania via delivery of plasmid libraries.
Increased intestinal permeability and inflammation, both fueled by dysbiosis, appear to contribute to rheumatoid arthritis (RA) pathogenesis. This single-center pilot study aimed to investigate zonulin, a marker of intestinal permeability, and calprotectin, a marker of intestinal inflammation, measured in serum and fecal samples of RA patients using commercially available kits. We also analyzed plasma lipopolysaccharide (LPS) levels, a marker of intestinal permeability and inflammation. Furthermore, univariate, and multivariate regression analyses were carried out to determine whether or not there were associations of zonulin and calprotectin with LPS, BMI, gender, age, RA-specific parameters, fiber intake, and short-chain fatty acids in the gut. Serum zonulin levels were more likely to be abnormal with a longer disease duration and fecal zonulin levels were inversely associated with age. A strong association between fecal and serum calprotectin and between fecal calprotectin and LPS were found in males, but not in females, independent of other biomarkers, suggesting that fecal calprotectin may be a more specific biomarker than serum calprotectin is of intestinal inflammation in RA. Since this was a proof-of-principle study without a healthy control group, further research is needed to validate fecal and serum zonulin as valid biomarkers of RA in comparison with other promising biomarkers.
Making judgments of learning (JOLs) after studying can directly improve learning. This JOL reactivity has been shown for simple materials but has scarcely been investigated with educationally relevant materials such as expository texts. The few existing studies have not yet reported any consistent gains in text comprehension due to providing JOLs. In the present study, we hypothesized that increasing the chances of covert retrieval attempts when making JOLs after each of five to-be-studied text passages would produce comprehension benefits at 1 week compared to restudy. In a between-subjects design, we manipulated both whether participants (N = 210) were instructed to covertly retrieve the texts, and whether they made delayed target-absent JOLs. The results indicated that delayed, target-absent JOLs did not improve text comprehension after 1 week, regardless of whether prior instructions to engage in covert retrieval were provided. Based on the two-stage model of JOLs, we reasoned that participants’ retrieval attempts during metacomprehension judgments were either insufficient (i.e., due to a quick familiarity assessment) or were ineffective (e.g., due to low retrieval success).
Background: The COVID-19 pandemic has led to a flood of — often contradictory — evidence. HCWs had to develop strategies to locate information that supported their work. We investigated the information-seeking of different HCW groups in Germany. Methods: In December 2020, we conducted online surveys on COVID-19 information sources, strategies, assigned trustworthiness, and barriers — and in February 2021, on COVID-19 vaccination information sources. Results were analyzed descriptively; group comparisons were performed using χ\(^2\)-tests. Results: For general COVID-19-related medical information (413 participants), non-physicians most often selected official websites (57%), TV (57%), and e-mail/newsletters (46%) as preferred information sources — physicians chose official websites (63%), e-mail/newsletters (56%), and professional journals (55%). Non-physician HCWs used Facebook/YouTube more frequently. The main barriers were insufficient time and access issues. Non-physicians chose abstracts (66%), videos (45%), and webinars (40%) as preferred information strategy; physicians: overviews with algorithms (66%), abstracts (62%), webinars (48%). Information seeking on COVID-19 vaccination (2700 participants) was quite similar, however, with newspapers being more often used by non-physicians (63%) vs. physician HCWs (70%). Conclusion: Non-physician HCWs more often consulted public information sources. Employers/institutions should ensure the supply of professional, targeted COVID-19 information for different HCW groups.
PRO-Simat is a simulation tool for analysing protein interaction networks, their dynamic change and pathway engineering. It provides GO enrichment, KEGG pathway analyses, and network visualisation from an integrated database of more than 8 million protein-protein interactions across 32 model organisms and the human proteome. We integrated dynamical network simulation using the Jimena framework, which quickly and efficiently simulates Boolean genetic regulatory networks. It enables simulation outputs with in-depth analysis of the type, strength, duration and pathway of the protein interactions on the website. Furthermore, the user can efficiently edit and analyse the effect of network modifications and engineering experiments. In case studies, applications of PRO-Simat are demonstrated: (i) understanding mutually exclusive differentiation pathways in Bacillus subtilis, (ii) making Vaccinia virus oncolytic by switching on its viral replication mainly in cancer cells and triggering cancer cell apoptosis and (iii) optogenetic control of nucleotide processing protein networks to operate DNA storage. Multilevel communication between components is critical for efficient network switching, as demonstrated by a general census on prokaryotic and eukaryotic networks and comparing design with synthetic networks using PRO-Simat. The tool is available at https://prosimat.heinzelab.de/ as a web-based query server.
In recent years, various forms of caloric restriction (CR) and amino acid or protein restriction (AAR or PR) have shown not only success in preventing age-associated diseases, such as type II diabetes and cardiovascular diseases, but also potential for cancer therapy. These strategies not only reprogram metabolism to low-energy metabolism (LEM), which is disadvantageous for neoplastic cells, but also significantly inhibit proliferation. Head and neck squamous cell carcinoma (HNSCC) is one of the most common tumour types, with over 600,000 new cases diagnosed annually worldwide. With a 5-year survival rate of approximately 55%, the poor prognosis has not improved despite extensive research and new adjuvant therapies. Therefore, for the first time, we analysed the potential of methionine restriction (MetR) in selected HNSCC cell lines. We investigated the influence of MetR on cell proliferation and vitality, the compensation for MetR by homocysteine, the gene regulation of different amino acid transporters, and the influence of cisplatin on cell proliferation in different HNSCC cell lines.
Alveolar (AE) and cystic (CE) echinococcosis are two parasitic diseases caused by the tapeworms Echinococcus multilocularis and E. granulosus sensu lato (s. l.), respectively. Currently, AE and CE are mainly diagnosed by means of imaging techniques, serology, and clinical and epidemiological data. However, no viability markers that indicate parasite state during infection are available. Extracellular small RNAs (sRNAs) are short non-coding RNAs that can be secreted by cells through association with extracellular vesicles, proteins, or lipoproteins. Circulating sRNAs can show altered expression in pathological states; hence, they are intensively studied as biomarkers for several diseases. Here, we profiled the sRNA transcriptomes of AE and CE patients to identify novel biomarkers to aid in medical decisions when current diagnostic procedures are inconclusive. For this, endogenous and parasitic sRNAs were analyzed by sRNA sequencing in serum from disease negative, positive, and treated patients and patients harboring a non-parasitic lesion. Consequently, 20 differentially expressed sRNAs associated with AE, CE, and/or non-parasitic lesion were identified. Our results represent an in-depth characterization of the effect E. multilocularis and E. granulosus s. l. exert on the extracellular sRNA landscape in human infections and provide a set of novel candidate biomarkers for both AE and CE detection.
Grading, immunohistochemistry and c-kit mutation status are criteria for assessing the prognosis and therapeutic options of canine cutaneous mast cell tumours (MCTs). As a subset, canine digital MCTs have rarely been explored in this context. Therefore, in this retrospective study, 68 paraffin-embedded canine digital MCTs were analysed, and histological grading was assessed according to Patnaik and Kiupel. The immunohistochemical markers KIT and Ki67 were used, as well as polymerase chain reaction (PCR) for mutational screening in c-kit exons 8, 9, 11 and 14. Patnaik grading resulted in 22.1% grade I, 67.6% grade II and 10.3% grade III tumours. Some 86.8% of the digital MCTs were Kiupel low-grade. Aberrant KIT staining patterns II and III were found in 58.8%, and a count of more than 23 Ki67-positive cells in 52.3% of the cases. Both parameters were significantly associated with an internal tandem duplication (ITD) in c-kit exon 11 (12.7%). French Bulldogs, which tend to form well-differentiated cutaneous MCTs, had a higher proportion of digital high-grade MCTs and ITD in c-kit exon 11 compared with mongrels. Due to its retrospective nature, this study did not allow for an analysis of survival data. Nevertheless, it may contribute to the targeted characterisation of digital MCTs.
Improved wall temperature prediction for the LUMEN rocket combustion chamber with neural networks
(2023)
Accurate calculations of the heat transfer and the resulting maximum wall temperature are essential for the optimal design of reliable and efficient regenerative cooling systems. However, predicting the heat transfer of supercritical methane flowing in cooling channels of a regeneratively cooled rocket combustor presents a significant challenge. High-fidelity CFD calculations provide sufficient accuracy but are computationally too expensive to be used within elaborate design optimization routines. In a previous work it has been shown that a surrogate model based on neural networks is able to predict the maximum wall temperature along straight cooling channels with convincing precision when trained with data from CFD simulations for simple cooling channel segments. In this paper, the methodology is extended to cooling channels with curvature. The predictions of the extended model are tested against CFD simulations with different boundary conditions for the representative LUMEN combustor contour with varying geometries and heat flux densities. The high accuracy of the extended model’s predictions, suggests that it will be a valuable tool for designing and analyzing regenerative cooling systems with greater efficiency and effectiveness.