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Abstract Single-cell and spatial technologies that profile gene expression across a whole tissue are revolutionizing the resolution of molecular states in clinical samples. Current commercially available technologies provide whole transcriptome single-cell, whole transcriptome spatial, or targeted in situ gene expression analysis. Here, we combine these technologies to explore tissue heterogeneity in large, FFPE human breast cancer sections. This integrative approach allowed us to explore molecular differences that exist between distinct tumor regions and to identify biomarkers involved in the progression towards invasive carcinoma. Further, we study cell neighborhoods and identify rare boundary cells that sit at the critical myoepithelial border confining the spread of malignant cells. Here, we demonstrate that each technology alone provides information about molecular signatures relevant to understanding cancer heterogeneity; however, it is the integration of these technologies that leads to deeper insights, ushering in discoveries that will progress oncology research and the development of diagnostics and therapeutics.

Abstract Flow processing offers many opportunities to optimize reactions in a rapid and automated manner, yet often requires relatively large quantities of input materials. To combat this, the use of a flexible slug flow reactor, equipped with two analytical instruments, for low‐volume optimization experiments are reported. A Buchwald–Hartwig amination toward the drug olanzapine, with 6 independent optimizable variables, is optimized using three different automated approaches: self‐optimization, design of experiments, and kinetic modeling. These approaches are complementary and provide differing information on the reaction: pareto optimal operating points, response surface models, and mechanistic models, respectively. The results are achieved using

This contribution focuses on the role of the literary and cultural imagination in constructing alternative imaginaries of the planet which exceed the purely economic dimension of the global and globalization and are open to different modes of knowing and doing. Expanding on Erin Wunker’s suggestion of a planetary poetics as an aesthetic mode with which to think and write across multiple spatial and temporal scales and engage with the ethical implications of living in a globalized world, this article looks at Kaie Kellough’s Magnetic Equator (2019) and its neo-cosmopolitan tidalectics as planetary poetics.

Abstract Background Fusions of neurotrophic tropomyosin receptor kinase genes NTRK1, NTRK2 and NTRK3 with various partner genes occur in both common and rare tumours and are of paramount predictive value due to the availability of very effective pan-Trk inhibitors like Larotrectinib and Entrectinib. Detection of NTRK fusions is mainly performed by fluorescence in situ hybridization (FISH) and next generation sequencing (NGS). The case described here showed a very unusual, but highly significant FISH signal pattern with an NTRK3 break apart probe, indicative of a functional NTRK3 rearrangement. Case presentation We describe here the case of a male patient who was originally diagnosed with an adenocarcinoma of the parotid gland without evidence of metastases. After the development of multiple lung metastases, an extensive immunohistochemical and molecular examination of archived tumour tissue including analysis of NTRK was performed. NTRK expression was detected by immunohistochemistry (IHC) and then comprehensively analysed further by FISH, quantitative reverse transcription PCR (RT-qPCR), and NGS. NTRK3 break apart FISH showed multiple and very faint single 3′ signals in addition to fusion signals. Quantitative reverse transcription PCR and NGS confirmed an ETV6:exon5-NTRK3:exon15 fusion. Diagnosis was therefore revised to metastatic secretory carcinoma of the salivary gland, and the patient subsequently treated with Larotrectinib, resulting in persisting partial remission. Conclusions Our findings underline the importance to be aware of non-canonical signal patterns during FISH analysis for detection of NTRK rearrangements. Very faint single 3′ signals can indicate a functional NTRK rearrangement and therefore be of high predictive value.

Abstract Background Inferring phylogenetic relationships of polyploid species and their diploid ancestors (leading to reticulate phylogenies in the case of an allopolyploid origin) based on multi-locus sequence data is complicated by the unknown assignment of alleles found in polyploids to diploid subgenomes. A parsimony-based approach to this problem has been proposed by Oberprieler et al. (Methods Ecol Evol 8:835–849, 2017), however, its implementation is of limited practical value. In addition to previously identified shortcomings, it has been found that in some cases, the obtained results barely satisfy the applied criterion. To be of better use to other researchers, a reimplementation with methodological refinement appears to be indispensable. Results We present the AllCoPol package, which provides a heuristic method for assigning alleles from polyploids to diploid subgenomes based on the Minimizing Deep Coalescences (MDC) criterion in multi-locus sequence datasets. An additional consensus approach further allows to assess the confidence of phylogenetic reconstructions. Simulations of tetra- and hexaploids show that under simplifying assumptions such as completely disomic inheritance, the topological errors of reconstructed phylogenies are similar to those of MDC species trees based on the true allele partition. Conclusions AllCoPol is a Python package for phylogenetic reconstructions of polyploids offering enhanced functionality as well as improved usability. The included methods are supplied as command line tools without the need for prior programming knowledge.

Introduction to the Thematic Issue.

Abstract Background Tumors in radiologically dense breast were overlooked on mammograms more often than tumors in low-density breasts. A fast reproducible and automated method of assessing percentage mammographic density (PMD) would be desirable to support decisions whether ultrasonography should be provided for women in addition to mammography in diagnostic mammography units. PMD assessment has still not been included in clinical routine work, as there are issues of interobserver variability and the procedure is quite time consuming. This study investigated whether fully automatically generated texture features of mammograms can replace time-consuming semi-automatic PMD assessment to predict a patient’s risk of having an invasive breast tumor that is visible on ultrasound but masked on mammography (mammography failure). Methods This observational study included 1334 women with invasive breast cancer treated at a hospital-based diagnostic mammography unit. Ultrasound was available for the entire cohort as part of routine diagnosis. Computer-based threshold PMD assessments (“observed PMD”) were carried out and 363 texture features were obtained from each mammogram. Several variable selection and regression techniques (univariate selection, lasso, boosting, random forest) were applied to predict PMD from the texture features. The predicted PMD values were each used as new predictor for masking in logistic regression models together with clinical predictors. These four logistic regression models with predicted PMD were compared among themselves and with a logistic regression model with observed PMD. The most accurate masking prediction was determined by cross-validation. Results About 120 of the 363 texture features were selected for predicting PMD. Density predictions with boosting were the best substitute for observed PMD to predict masking. Overall, the corresponding logistic regression model performed better (cross-validated AUC, 0.747) than one without mammographic density (0.734), but less well than the one with the observed PMD (0.753). However, in patients with an assigned mammography failure risk >10%, covering about half of all masked tumors, the boosting-based model performed at least as accurately as the original PMD model. Conclusion Automatically generated texture features can replace semi-automatically determined PMD in a prediction model for mammography failure, such that more than 50% of masked tumors could be discovered.

OBJECTIVE:The aim of this study was to evaluate the influence of implant diameter, length and shape on a surrogate parameter of implant survival; i.e. the implant return rate in a big data analysis. MATERIALS AND METHODS:A retrospective study was conducted and the factors influencing the success rates of 69,377 sold implants over a seven-year period were evaluated. The osseointegration program of a reseller provides reliable data of a single country. Implant loss rates were investigated using logistic regression models and regressed by implant type, diameter, and length. RESULTS:The return rate of 69,377 sold implants was 2.78% and comparable to implant loss rates in previous published prospective studies as its surrogate parameter. A total of 80% of implant returns had occurred within 157 days, and an additional 15% within 750.25 days. Diameters of 3.8 to 5.0mm showed the lowest return rates with its bottom in the 4.3mm implant whilst 6.0mm implants had significantly higher return rates. In comparison to the most sold implant length (13mm) shorter implants showed significantly higher early return rates. CONCLUSIONS:The study provides evidence that in cases of standard indications and sufficient bone, the use of screw typed dental implants with 3.8 or 4.3 diameter and 11 or 13 mm length shows the lowest implant return rates. Other implants may be selected only in specific indications.

High-throughput sequencing has allowed for unprecedented detail in gene expression analyses, yet its efficient application to single cells is challenged by the small starting amounts of RNA. We have developed CEL-Seq, a method for overcoming this limitation by barcoding and pooling samples before linearly amplifying mRNA with the use of one round of in vitro transcription. We show that CEL-Seq gives more reproducible, linear, and sensitive results than a PCR-based amplification method. We demonstrate the power of this method by studying early C. elegans embryonic development at single-cell resolution. Differential distribution of transcripts between sister cells is seen as early as the two-cell stage embryo, and zygotic expression in the somatic cell lineages is enriched for transcription factors. The robust transcriptome quantifications enabled by CEL-Seq will be useful for transcriptomic analyses of complex tissues containing populations of diverse cell types.

Cigarette smoking (CS) aggravates post-traumatic acute lung injury and increases ventilator-induced lung injury due to more severe tissue inflammation and apoptosis. Hyper-inflammation after chest trauma is due to the physical damage, the drop in alveolar PO2, and the consecutive hypoxemia and tissue hypoxia. Therefore, we tested the hypotheses that 1) CS exposure prior to blunt chest trauma causes more severe post-traumatic inflammation and thereby aggravates lung injury, and that 2) hyperoxia may attenuate this effect. Immediately after blast wave-induced blunt chest trauma, mice (n=32) with or without 3-4 weeks of CS exposure underwent 4 hours of pressure-controlled, thoraco-pulmonary compliance-titrated, lung-protective mechanical ventilation with air or 100% O2. Hemodynamics, lung mechanics, gas exchange, and acid-base status were measured together with blood and tissue cytokine and chemokine concentrations, heme oxygenase-1 (HO-1), activated caspase-3, and hypoxia-inducible factor 1-α (HIF-1α) expression, nuclear factor-κB (NF-κB) activation, nitrotyrosine formation, purinergic receptor 2X4 (P2XR4) and 2X7 (P2XR7) expression, and histological scoring. CS exposure prior to chest trauma lead to higher pulmonary compliance and lower PaO2 and Horovitz-index, associated with increased tissue IL-18 and blood MCP-1 concentrations, a 2-4-fold higher inflammatory cell infiltration, and more pronounced alveolar membrane thickening. This effect coincided with increased activated caspase-3, nitrotyrosine, P2XR4, and P2XR7 expression, NF-κB activation, and reduced HIF-1α expression. Hyperoxia did not further affect lung mechanics, gas exchange, pulmonary and systemic cytokine and chemokine concentrations, or histological scoring, except for some patchy alveolar edema in CS exposed mice. However, hyperoxia attenuated tissue HIF-1α, nitrotyrosine, P2XR7, and P2XR4 expression, while it increased HO-1 formation in CS exposed mice. Overall, CS exposure aggravated post-traumatic inflammation, nitrosative stress and thereby organ dysfunction and injury; short-term, lung-protective, hyperoxic mechanical ventilation have no major beneficial effect despite attenuation of nitrosative stress, possibly due to compensation of by regional alveolar hypoxia and/or consecutive hypoxemia, resulting in down-regulation of HIF-1α expression.

Genome-wide expression profiling is a widely used approach for characterizing heterogeneous populations of cells, tissues, biopsies, or other biological specimen. The exploratory analysis of such data typically relies on generic unsupervised methods, e.g. principal component analysis (PCA) or hierarchical clustering. However, generic methods fail to exploit prior knowledge about the molecular functions of genes. Here, I introduce GO-PCA, an unsupervised method that combines PCA with nonparametric GO enrichment analysis, in order to systematically search for sets of genes that are both strongly correlated and closely functionally related. These gene sets are then used to automatically generate expression signatures with functional labels, which collectively aim to provide a readily interpretable representation of biologically relevant similarities and differences. The robustness of the results obtained can be assessed by bootstrapping.I first applied GO-PCA to datasets containing diverse hematopoietic cell types from human and mouse, respectively. In both cases, GO-PCA generated a small number of signatures that represented the majority of lineages present, and whose labels reflected their respective biological characteristics. I then applied GO-PCA to human glioblastoma (GBM) data, and recovered signatures associated with four out of five previously defined GBM subtypes. My results demonstrate that GO-PCA is a powerful and versatile exploratory method that reduces an expression matrix containing thousands of genes to a much smaller set of interpretable signatures. In this way, GO-PCA aims to facilitate hypothesis generation, design of further analyses, and functional comparisons across datasets.

In polytrauma patients a thoracic trauma is one of the most critical injuries and an important trigger of post-traumatic inflammation. About 50% of patients with thoracic trauma are additionally affected by bone fractures. The risk for fracture malunion is considerably increased in such patients, the pathomechanisms being poorly understood. Thoracic trauma causes regional alveolar hypoxia and, subsequently, hypoxemia, which in turn triggers local and systemic inflammation. Therefore, we aimed to unravel the role of oxygen in impaired bone regeneration after thoracic trauma. We hypothesized that short-term breathing of 100% oxygen in the early post-traumatic phase ameliorates inflammation and improves bone regeneration. Mice underwent a femur osteotomy alone or combined with blunt chest trauma 100% oxygen was administered immediately after trauma for two separate 3 hour intervals. Arterial blood gas tensions, microcirculatory perfusion and oxygenation were assessed at 3, 9 and 24 hours after injury. Inflammatory cytokines and markers of oxidative/nitrosative stress were measured in plasma, lung and fracture hematoma. Bone healing was assessed on day 7, 14 and 21. Thoracic trauma induced pulmonary and systemic inflammation and impaired bone healing. Short-term exposure to 100% oxygen in the acute post-traumatic phase significantly attenuated systemic and local inflammatory responses and improved fracture healing without provoking toxic side effects, suggesting that hyperoxia could induce anti-inflammatory and pro-regenerative effects after severe injury. These results suggest that breathing of 100% oxygen in the acute post-traumatic phase might reduce the risk of poorly healing fractures in severely injured patients.

Crohn disease (CD), a sub-entity of inflammatory bowel disease (IBD), is a complex polygenic disorder. Although recent studies have successfully identified CD-associated genetic variants, these susceptibility loci explain only a fraction of the heritability of the disease. Here, we report on a multi-stage genome-wide scan of 393 German CD cases and 399 controls. Among the 116,161 single-nucleotide polymorphisms tested, an association with the known CD susceptibility gene NOD2, the 5q31 haplotype, and the recently reported CD locus at 5p13.1 was confirmed. In addition, SNP rs1793004 in the gene encoding nel-like 1 precursor (NELL1, chromosome 11p15.1) showed a consistent disease-association in independent German population- and family-based samples (942 cases, 1082 controls, 375 trios). Subsequent fine mapping and replication in an independent sample of 454 French/Canadian CD trios supported the authenticity of the NELL1 association. Further confirmation in a large German ulcerative colitis (UC) sample indicated that NELL1 is a ubiquitous IBD susceptibility locus (combined p

The article discusses the challenges faced by the European Commission in enforcing antitrust laws in digital markets with network effects. It emphasizes the role of National Competition Authorities (NCAs) and private claimants in complementing the Commission's efforts, but acknowledges the constraints imposed by EU regulations. The article also explores the Digital Markets Act (DMA) and its aim to harmonize regulatory solutions at the national level. It compares the DMA with the German Act Against Restraints of Competition (ARC) and highlights differences in obligations and enforcement. The article concludes by suggesting the need for a more consistent approach that embraces diversity before harmonization. [Extracted from the article]

The article is a book review of "Regulation 1/2003 and EU Antitrust Enforcement: A Systematic Guide." The book provides a comprehensive analysis of EU competition law enforcement, including a detailed commentary on Regulation 1/2003. It also offers a normative assessment of the current law and identifies potential issues for future reform. The book includes contributions from a wide range of experts, including judges, officials, academics, and practitioners. It is recommended for anyone interested in EU competition law enforcement and is considered a valuable resource for both academics and practitioners. [Extracted from the article]