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Brain collateral circulation is an essential compensatory mechanism in response to acute brain ischemia. To study the temporal evolution of brain macro and microcollateral recruitment and their reciprocal interactions in response to different ischemic conditions, we applied a combination of complementary techniques (T2-weighted magnetic resonance imaging [MRI], time of flight [TOF] angiography [MRA], cerebral blood flow [CBF] imaging and histology) in two different mouse models. Hypoperfusion was either induced by permanent bilateral common carotid artery stenosis (BCCAS) or 60-min transient unilateral middle cerebral artery occlusion (MCAO). In both models, collateralization is a very dynamic phenomenon with a global effect affecting both hemispheres. Patency of ipsilateral posterior communicating artery (PcomA) represents the main variable survival mechanism and the main determinant of stroke lesion volume and recovery in MCAO, whereas the promptness of external carotid artery retrograde flow recruitment together with PcomA patency, critically influence survival, brain ischemic lesion volume and retinopathy in BCCAS mice. Finally, different ischemic gradients shape microcollateral density and size.

VarFish is a user-friendly web application for the quality control, filtering, prioritization, analysis, and user-based annotation of panel and exome variant data for rare disease genetics. It is capable of processing variant call files with single or multiple samples. The variants are automatically annotated with population frequencies, molecular impact, and presence in databases such as ClinVar. Further, it provides support for pathogenicity scores including CADD, MutationTaster, and phenotypic similarity scores. Users can filter variants based on these annotations and presumed inheritance pattern and sort the results by these scores. Filtered variants are listed with their annotations and many useful link-outs to genome browsers, other gene/variant data portals, and external tools for variant assessment. VarFish allows user to create their own annotations including support for variant assessment following ACMG-AMP guidelines. In close collaboration with medical practitioners, VarFish was designed for variant analysis and prioritization in diagnostic and research settings as described in the software’s extensive manual. The user interface has been optimized for supporting these protocols. Users can install VarFish on their own in-house servers where it provides additional lab notebook features for collaborative analysis and allows re-analysis of cases, e.g., after update of genotype or phenotype databases.

In colorectal cancer, oncogenic mutations transform a hierarchically organized and homeostatic epithelium into invasive cancer tissue lacking visible organization. We sought to define colorectal cancer cell types and signals controlling their development. More than 30,000 epithelial single cell transcriptomes of tumors and matched non-cancerous tissues of twelve colorectal cancer patients were clustered into six patient-overarching groups defined by differential activities of oncogenic signaling pathways such as mitogen-activated protein kinase and oncogenic traits such as replication stress. RNA metabolic labeling and assessment of RNA velocity in patient-derived organoids revealed developmental trajectories of colorectal cancer cells organized along a mitogen-activated protein kinase activity gradient. This was in contrast to normal colon organoid cells developing along graded Wnt activity. Experimental targeting of EGFR-BRAF-MEK in cancer organoids affected signaling and gene expression contingent on predictive KRAS/BRAF mutations and induced cell plasticity overriding default developmental trajectories, providing a basis for non-genetic resistance to targeted therapies.

SARS-CoV-2 utilizes the ACE2 transmembrane peptidase as essential cellular entry receptor. Several studies have suggested abundant ACE2 expression in the human lung, inferring strong permissiveness to SARS-CoV-2 infection with resultant alveolar damage and lung injury. Against this expectation, we provide evidence that ACE2 expression must be considered scarce, thereby limiting SARS-CoV-2 propagation in the human alveolus. Instead, spectral imaging of ex vivo infected human lungs and COVID-19 autopsy samples depicted that alveolar macrophages were frequently positive for SARS-CoV-2, indicating viral phagocytosis. Single-cell transcriptomics of SARS-CoV-2 infected human lung tissue further revealed strong inflammatory and anti-viral activation responses in macrophages and monocytes, comparable to those induced by MERS-CoV, but with virus-specific gene expression profiles. Collectively, our findings indicate that severe lung injury in COVID-19 likely results from an overwhelming immune activation rather than direct viral damage of the alveolar compartment. Funding: ACH, LES, SH were supported by Berlin University Alliance GC2 Global Health (Corona Virus Pre-Exploration Project). ACH, SH, TW and CD were supported by BMBF (RAPID) and ACH, SH by BMBF (alvBarriereCOVID-19). KH, LB, SL, SH, CD, TW, ACH were funded by BMBF (NFN-COVID 19, Organo-Strat). KH, NS, LES, MW, SH, ADG, CD, TW and ACH were supported by DFG (SFB-TR 84). ACH was supported by BIH, Charite 3R, and Charite-Zeiss MultiDim. KH was supported by BMBF (Camo-COVID-19). MW, NS and SH was supported by BMBF (PROVID). MW and NS was supported by BIH and BMBF (SYMPATH, CAPSyS, NAPKON). BO and DB were funded through the BIH Clinical Single Cell Bioinformatics Pipeline. LB was supported by the BMBF (CoIMMUNE), the DFG (KFO 342) and the IZKF of the Medical Faculty of the WWU. Conflict of Interest: The authors declare no competing interests. Ethical Approval: The study was approved by the ethics committee at the Charite clinic (projects EA2/079/13) and Arztekammer Westfalen-Lippe and of the Westfalischen Wilhelms-Universitat (AZ: 2016-265-f-S). Written informed consent was obtained from all patients.

Background Reliable and reproducible interpretation of molecular aberrations constitutes a bottleneck of precision medicine. Evidence-based decision management systems may improve rational therapy recommendations. To cope with an increasing amount of complex molecular data in the clinical care of patients with cancer, we established a workflow for the interpretation of molecular analyses. Methods A specialized physician screened results from molecular analyses for potential biomarkers, irrespective of the diagnostic modality. Best available evidence was retrieved and categorized through establishment of an in-house database and interrogation of publicly available databases. Annotated biomarkers were ranked using predefined evidence levels and subsequently discussed at a molecular tumour board (MTB), which generated treatment recommendations. Subsequent translation into patient treatment and clinical outcomes were followed up. Results One hundred patients were discussed in the MTB between January 2016 and May 2017. Molecular data were obtained for 70 of 100 patients (50 whole exome/RNA sequencing, 18 panel sequencing, 2 immunohistochemistry (IHC)/microsatellite instability analysis). The MTB generated a median of two treatment recommendations each for 63 patients. Thirty-nine patients were treated: 6 partial responses and 12 stable diseases were achieved as best responses. Genetic counselling for germline events was recommended for seven patients. Conclusion The development of an evidence-based workflow allowed for the clinical interpretation of complex molecular data and facilitated the translation of personalized treatment strategies into routine clinical care. The high number of treatment recommendations in patients with comprehensive genomic data and promising responses in patients treated with combination therapy warrant larger clinical studies.

Allogeneic hematopoietic stem cell transplantation (alloHSCT) is the only curative treatment option for various malignant hematological diseases. The therapeutic effect of alloHSCT is a long-lasting graft-versus-leukemia (GvL) effect of the transferred graft. T cells are important mediators of GvL and the longitudinal tracking of T-cell clones from donor to recipient is of particular interest in the setting of alloHSCT as this might provide further insight into mechanisms leading to survival and expansion of particular clones. In a broader sense, we used the unique setting of alloHSCT to study survival and expansion of mature T-cell clones after transfer into an immune cell depleted and allogeneic patient. We used single-cell RNA sequencing (scRNAseq) to integrate immune subset delineation, clone identification and transcriptome information of about 35500 single T cells in peripheral blood of 14 paired donor-recipient samples in four alloHSCT pairs. Donor samples were collected before and after treatment with Granulocyte-Colony Stimulating Factor (GCSF), and recipient samples were collected on days +90 and +180 post-transplant. Looking at common diversity scores of pooled donor versus pooled recipient time points we observe an expected decrease of TCR diversity after transplantation (median inv. Simpson's 379 in donor vs. 20 in recipient samples, p=0.011, Figure 1A). On single cell level, we observe a substantial decrease of unique T-cell clones after transplantation compared to donor samples, which in return means that certain TCR clones markedly expand, contributing to a skewing of the TCR repertoire in the post-transplant course. The majority of these cells represent CD8 effector memory T cells. Our main interest was a better understanding of traceable and persisting T-cell clones. In a first step, we looked at the overall clonal overlap between time points of the different donor-recipient pairs, using only combined TCR alpha and beta chain information to define specific T-cell clones. We find the highest overlaps of T-cell clones between time points within individuals (e.g., Morisita score 0.91 between preGCSF and postGCSF of donor 16 and Morisita score 0.65 between days +90 and +180 of recipient 16, Figure 1B). Additionally, we demonstrate an inter-individual overlap between donors and their respective recipients in all pairs on single cell level (Figure 1C). Next, we compared the differential gene expression of traceable and non-traceable T cell clones and found that the traceable T cell clones exhibit a distinct transcriptional program, characterized by upregulation of genes related to T cell proliferation and chemotaxis as well as antigen presentation, while housekeeping functions such as translation are downregulated. In order to examine the dynamic changes of the T-cell transcriptome, we looked at the differential gene expression at the consecutive time points of pooled traceable clones in all pairs. This shows an induction of an activation pattern during the donor-recipient transfer and post-transplant phase involving genes related to the cell cycle and graft-versus-host disease (Figure 1D). Phenotype analysis via antibody-derived tags accordingly revealed an upregulation of activation markers in the recipients. To our knowledge, this is the first time that longitudinal inter-individual (donor-to-recipient) overlap of single-cell TCR alpha/beta clones is demonstrated in the setting of alloHSCT revealing time point-dependent and distinct functional patterns in traceable donor T cell clones. Figure 1 Figure 1. Disclosures Penack: Neovii: Honoraria; MSD: Honoraria; Incyte: Research Funding; Priothera: Consultancy; Therakos: Honoraria; Gilead: Honoraria; Novartis: Honoraria; Pfizer: Honoraria; Takeda: Research Funding; Astellas: Honoraria; Jazz: Honoraria; Omeros: Consultancy; Shionogi: Consultancy. Bullinger: Amgen: Honoraria; Jazz Pharmaceuticals: Consultancy, Honoraria, Research Funding; Hexal: Consultancy; Abbvie: Consultancy, Honoraria; Bristol-Myers Squibb: Consultancy, Honoraria; Astellas: Honoraria; Pfizer: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Bayer: Research Funding; Seattle Genetics: Honoraria; Novartis: Consultancy, Honoraria; Daiichi Sankyo: Consultancy, Honoraria; Menarini: Consultancy; Gilead: Consultancy; Celgene: Consultancy, Honoraria; Sanofi: Honoraria. Na: Bristol Myers Squibb: Research Funding; Shire/Takeda: Honoraria, Research Funding; Octapharma: Honoraria, Research Funding.

Chemotherapy-induced peripheral neuropathy (CIPN) is a frequent, potentially irreversible adverse effect of cytotoxic chemotherapy often leading to a reduction or discontinuation of treatment which negatively impacts patients' prognosis. To date, however, neither predictive biomarkers nor preventive treatments for CIPN are available, which is partially due to a lack of suitable experimental models. We therefore aimed to evaluate whether sensory neurons derived from induced pluripotent stem cells (iPSC-DSN) can serve as human disease model system for CIPN. Treatment of iPSC-DSN for 24 h with the neurotoxic drugs paclitaxel, bortezomib, vincristine and cisplatin led to axonal blebbing and a dose dependent decline of cell viability in clinically relevant IC50 ranges, which was not observed for the non-neurotoxic compounds doxorubicin and 5-fluorouracil. Paclitaxel treatment effects were less pronounced after 24 h but prominent when treatment was applied for 72 h. Global transcriptome analyses performed at 24 h, i.e. before paclitaxel-induced cell death occurred, revealed the differential expression of genes of neuronal injury, cellular stress response, and sterol pathways. We further evaluated if known neuroprotective strategies can be reproduced in iPSC-DSN and observed protective effects of lithium replicating findings from rodent dorsal root ganglia cells. Comparing sensory neurons derived from two different healthy donors, we found preliminary evidence that these cell lines react differentially to neurotoxic drugs as expected from the variable presentation of CIPN in patients. In conclusion, iPSC-DSN are a promising platform to study the pathogenesis of CIPN and to evaluate neuroprotective treatment strategies. In the future, the application of patient-specific iPSC-DSN could open new avenues for personalized medicine with individual risk prediction, choice of chemotherapeutic compounds and preventive treatments.

The relative contribution of the effector molecules produced by T cells to tumour rejection is unclear, but interferon-γ (IFNγ) is critical in most of the analysed models1. Although IFNγ can impede tumour growth by acting directly on cancer cells2,3, it must also act on the tumour stroma for effective rejection of large, established tumours4,5. However, which stroma cells respond to IFNγ and by which mechanism IFNγ contributes to tumour rejection through stromal targeting have remained unknown. Here we use a model of IFNγ induction and an IFNγ–GFP fusion protein in large, vascularized tumours growing in mice that express the IFNγ receptor exclusively in defined cell types. Responsiveness to IFNγ by myeloid cells and other haematopoietic cells, including T cells or fibroblasts, was not sufficient for IFNγ-induced tumour regression, whereas responsiveness of endothelial cells to IFNγ was necessary and sufficient. Intravital microscopy revealed IFNγ-induced regression of the tumour vasculature, resulting in arrest of blood flow and subsequent collapse of tumours, similar to non-haemorrhagic necrosis in ischaemia and unlike haemorrhagic necrosis induced by tumour necrosis factor. The early events of IFNγ-induced tumour ischaemia resemble non-apoptotic blood vessel regression during development, wound healing or IFNγ-mediated, pregnancy-induced remodelling of uterine arteries6–8. A better mechanistic understanding of how solid tumours are rejected may aid the design of more effective protocols for adoptive T-cell therapy.

BackgroundSingle cell omics technologies present unique opportunities for biomedical and life sciences from lab to clinic, but the high dimensional nature of such data poses challenges for computational analysis and interpretation. Furthermore, FAIR data management as well as data privacy and security become crucial when working with clinical data, especially in cross-institutional and translational settings. Existing solutions are either bound to the desktop of one researcher or come with dependencies on vendor-specific technology for cloud storage or user authentication.ResultsTo facilitate analysis and interpretation of single-cell data by users without bioinformatics expertise, we present SCelVis, a flexible, interactive and user-friendly app for web-based visualization of pre-processed single-cell data. Users can survey multiple interactive visualizations of their single cell expression data and cell annotation, and download raw or processed data for further offline analysis. SCelVis can be run both on the desktop and cloud systems, accepts input from local and various remote sources using standard and open protocols, and allows for hosting data in the cloud and locally.MethodsSCelVis is implemented in Python using Dash by Plotly. It is available as a standalone application as a Python package, via Conda/Bioconda and as a Docker image. All components are available as open source under the permissive MIT license and are based on open standards and interfaces, enabling further development and integration with third party pipelines and analysis components. The GitHub repository is https://github.com/bihealth/scelvis.

High false positive rates in GC-MS metabolomics peak detection is a common issue that impedes automated analysis of large-scale datasets. There is a growing need for improving the reliability and scalability of data analysis workflows. Many algorithms are available for peak detection [1], a crucial step for the data analysis, but performance and outcome can differ widely depending on both algorithmic approach and data acquisition method. This makes it difficult to compare and contrast between algorithms without extensive manual intervention.nnWe present a workflow for improved peak picking (WiPP), a parameter optimizing, multi-algorithm peak detection workflow for GC-MS metabolomics, which automatically evaluates the quality of detected peaks using machine learning-based classification. First, the classifier is trained to distinguish between real compound related peaks and false positive peaks. Then the algorithm parameters are scored based on the quality of detected peaks and optimized accordingly. This procedure is repeated for two peak detection algorithms and subsequently both algorithms are run in parallel on the entire data set with the optimized parameters. The qualitative information returned by the classifier for every peak is then used to merge individual algorithm results into one final high confidence peak set.nnUsing this approach, we show that automated detection and evaluation of peak quality is improved. The additional quantitative and qualitative information generated by the classifier allows:nnO_LIa novel way to classify peaks based on seven classes and thus objectively to assess their qualitynC_LIO_LIimpartial performance comparison of different peak picking algorithmsnC_LIO_LIautomated parameter optimization for each individual peak picking algorithmnC_LIO_LIa final, improved high quality peak list to be generated for statistical or further analyses.nC_LInnIt achieves this while minimising the operator-time required by packaging this within a fully automated workflow. The modular design allows extension, adjustment and improvement of the workflow using different or additional peak detection algorithms and classifiers. Importantly, due to the fully automated implementation, the workflow is suitable for large-scale studies.nnThe pipeline supports mzML, mzData and NetCDF formats and is implemented in python using snakemake, a reproducible and scalable workflow management system, it is available on GitHub (https://github.com/bihealth/WiPP).

Summary. Managing raw sequencing data and conversion into sequences (demultiplexing) remains a challenging topic for groups running sequencing devices. They face many challenges in such efforts and solutions range from manual management of spreadsheets to very complex and customized LIMS systems handling much more than just sequencing raw data. In this manuscript, we describe the software package DigestiFlow that focuses on the management of Illumina flow cell sample sheets and raw data. Namely, it allows for automated extraction of flow cell raw data information, management of sample sheets, and the automated (and thus reproducible) demultiplexing of Illumina base calls data. Availability and Implementation. The software is available under the MIT license at https://github.com/bihealth/digestiflow-server. The client and demux software components are available via Bioconda.

Accurate modeling of intratumor heterogeneity presents a bottleneck against drug testing. Flexibility in a preclinical platform is also desirable to support assessment of different endpoints. We established the model system, OHC-NB1, from a bone marrow metastasis from a patient diagnosed with MYCN-amplified neuroblastoma and performed whole-exome sequencing on the source metastasis and the different models and passages during model development (monolayer cell line, 3D spheroid culture and subcutaneous xenograft tumors propagated in mice). OHC-NB1 harbors a MYCN amplification in double minutes, 1p deletion, 17q gain and diploid karyotype, which persisted in all models. A total of 80-540 single-nucleotide variants (SNVs) was detected in each sample, and comparisons between the source metastasis and models identified 34 of 80 somatic SNVs to be propagated in the models. Clonal reconstruction using the combined copy number and SNV data revealed marked clonal heterogeneity in the originating metastasis, with four clones being reflected in the model systems. The set of OHC-NB1 models represents 43% of somatic SNVs and 23% of the cellularity in the originating metastasis with varying clonal compositions, indicating that heterogeneity is partially preserved in our model system.

Immune checkpoint inhibition leads to response in some patients with head and neck squamous cell carcinoma (HNSCC). Robust biomarkers are lacking to date. We analyzed viral status, gene expression signatures, mutational load and mutational signatures in whole exome and RNA-sequencing data of the HNSCC TCGA dataset (N = 496) and a validation set (DKTK MASTER cohort, N = 10). Public single-cell gene expression data from 17 HPV-negative HNSCC were separately re-analyzed. APOBEC3-associated TCW motif mutations but not total single nucleotide variant burden were significantly associated with inflammation. This association was restricted to HPV-negative HNSCC samples. An APOBEC-enriched, HPV-negative subgroup was identified, that showed higher T-cell inflammation and immune checkpoint expression, as well as expression of APOBEC3 genes. Mutations in immune-evasion pathways were also enriched in these tumors. Analysis of single-cell sequencing data identified expression of APOBEC3B and 3C genes in malignant cells. We identified an APOBEC-enriched subgroup of HPV-negative HNSCC with a distinct immunogenic phenotype, potentially mediating response to immunotherapy.

Self-propagating amyloid-β (Aβ) aggregates or seeds possibly drive pathogenesis of Alzheimer's disease (AD). Small molecules targeting such structures might act therapeutically in vivo. Here, a fluorescence polarization assay was established that enables the detection of compound effects on both seeded and spontaneous Aβ42 aggregation. In a focused screen of anti-amyloid compounds, we identified Disperse Orange 1 (DO1) ([4-((4-nitrophenyl)diazenyl)-N-phenylaniline]), a small molecule that potently delays both seeded and non-seeded Aβ42 polymerization at substoichiometric concentrations. Mechanistic studies revealed that DO1 disrupts preformed fibrillar assemblies of synthetic Aβ42 peptides and decreases the seeding activity of Aβ aggregates from brain extracts of AD transgenic mice. DO1 also reduced the size and abundance of diffuse Aβ plaques and decreased neuroinflammation-related gene expression changes in brains of 5xFAD transgenic mice. Finally, improved nesting behavior was observed upon treatment with the compound. Together, our evidence supports targeting of self-propagating Aβ structures with small molecules as a valid therapeutic strategy.

The underlying genetic mechanisms and early pathological events of children with primary cardiomyopathy (CMP) are insufficiently characterized. In this study, we aimed to characterize the mutational spectrum of primary CMP in a large cohort of patients ���18 years referred to a tertiary center. Eighty unrelated index patients with pediatric primary CMP underwent genetic testing with a panel-based next-generation sequencing approach of 89 genes. At least one pathogenic or probably pathogenic variant was identified in 30/80 (38%) index patients. In all CMP subgroups, patients carried most frequently variants of interest in sarcomere genes suggesting them as a major contributor in pediatric primary CMP. In MYH7, MYBPC3, and TNNI3, we identified 18 pathogenic/probably pathogenic variants (MYH7 n = 7, MYBPC3 n = 6, TNNI3 n = 5, including one homozygous (TNNI3 c.24+2T>A) truncating variant. Protein and transcript level analysis on heart biopsies from individuals with homozygous mutation of TNNI3 revealed that the TNNI3 protein is absent and associated with upregulation of the fetal isoform TNNI1. The present study further supports the clinical importance of sarcomeric mutation-not only in adult-but also in pediatric primary CMP. TNNI3 is the third most important disease gene in this cohort and complete loss of TNNI3 leads to severe pediatric CMP.

Protein synthesis must be finely tuned in the developing nervous system as the final essential step of gene expression. This study investigates the architecture of ribosomes from the neocortex during neurogenesis, revealing Ebp1 as a high-occupancy 60S peptide tunnel exit (TE) factor during protein synthesis at near-atomic resolution by cryoelectron microscopy (cryo-EM). Ribosome profiling demonstrated Ebp1-60S binding is highest during start codon initiation and N-terminal peptide elongation, regulating ribosome occupancy of these codons. Membrane-targeting domains emerging from the 60S tunnel, which recruit SRP/Sec61 to the shared binding site, displace Ebp1. Ebp1 is particularly abundant in the early-born neural stem cell (NSC) lineage and regulates neuronal morphology. Ebp1 especially impacts the synthesis of membrane-targeted cell adhesion molecules (CAMs), measured by pulsed stable isotope labeling by amino acids in cell culture (pSILAC)/bioorthogonal noncanonical amino acid tagging (BONCAT) mass spectrometry (MS). Therefore, Ebp1 is a central component of protein synthesis, and the ribosome TE is a focal point of gene expression control in the molecular specification of neuronal morphology during development.

Multiple myeloma is a malignancy of monoclonal plasma cells accumulating in the bone marrow. The critical influence of tumor-infiltrating T cells on disease control and therapeutic responses has been shown in a variety of malignancies, however, the role of multiple myeloma bone marrow-infiltrating T cells is incompletely understood. Although it has been shown that multiple myeloma neo-antigen-specific T cells can be expanded in vitro, little is known about functions and specificities of clonally expanded multiple myeloma-infiltrating bone marrow T cells. Here we asked at the single cell level whether clonally expanded T cells i) were detectable in multiple myeloma bone marrow and peripheral blood, ii) showed characteristic immune phenotypes, and iii) recognized antigens selectively presented on multiple myeloma cells. A total of 6,744 single bone marrow T cells from 13 treatment-naïve patients were index-sorted and sequenced using our methodologies for determination of paired T cell receptor (TCR) αβ sequences along with immune phenotype, transcription factor and cytokine expression. Clonal T cell expansion occurred predominantly within the CD8+ compartment. Phenotypes of clonally expanded T cells were distinctive of cytolytic effector differentiation and significantly different from non-expanded CD8+ T cells. Less than 25% of expanded CD8+ T cell clones expressed the immune checkpoint molecules programmed death-1 (PD-1), cytotoxic T lymphocyte antigen-4 (CTLA-4), or T cell immunoglobulin and mucin-domain containing-3 (TIM-3), while B and T lymphocyte attenuator (BTLA) was expressed on more than half of the expanded clones. Clonal T cell expansion did not correlate with neo-antigen load as determined by whole exome and RNA sequencing of purified multiple myeloma cells. Furthermore, peripheral blood TCRβ repertoire sequencing from five selected patients with substantial bone marrow T cell expansion identified 90% of expanded bone marrow T cell clones overlapping with peripheral blood. To determine whether clonally expanded bone marrow T cells recognized antigens selectively presented on multiple myeloma cells, 71 dominant TCRs from five selected patients with substantial clonal T cell expansion were re-expressed in 58α-β- T-hybridoma reporter T cells and co-incubated with CD38-enriched multiple myeloma cells from the same patients. Only one of these TCRs recognized antigens selectively presented on multiple myeloma cells and this TCR was not neo-antigen-specific. Hypothesizing that the target antigen was a non-mutated self-antigen, we could show that this TCR also recognized the plasma cell leukemia cell line U-266 in an HLA-A*02:01-restricted manner. In summary, clonally expanded T cells in multiple myeloma bone marrow of newly diagnosed patients show cytolytic effector differentiation. In the majority of patients, clonally expanded bone marrow T cells do not recognize antigens presented on multiple myeloma cells and are not neo-antigen-specific. Our findings are relevant for the design of future therapeutics and clinical trials. The identified TCR, which recognizes a multiple myeloma antigen shared with U-266 in an HLA-A*02:01-restricted manner, could be a promising candidate for T cell therapy. Disclosures Bullinger: Jazz Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Hexal: Membership on an entity's Board of Directors or advisory committees; Sanofi: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; Menarini: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Gilead: Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Membership on an entity's Board of Directors or advisory committees; Astellas: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees; Seattle Genetics: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Daiichi Sankyo: Membership on an entity's Board of Directors or advisory committees.

Summary: Microglia express Toll-like receptors (TLRs) that sense pathogen- and host-derived factors, including single-stranded RNA. In the brain, let-7 microRNA (miRNA) family members are abundantly expressed, and some have recently been shown to serve as TLR7 ligands. We investigated whether let-7 miRNA family members differentially control microglia biology in health and disease. We found that a subset of let-7 miRNA family members function as signaling molecules to induce microglial release of inflammatory cytokines, modulate antigen presentation, and attenuate cell migration in a TLR7-dependent manner. The capability of the let-7 miRNAs to control microglial function is sequence specific, mapping to a let-7 UUGU motif. In human and murine glioblastoma/glioma, let-7 miRNAs are differentially expressed and reduce murine GL261 glioma growth in the same sequence-specific fashion through microglial TLR7. Taken together, these data establish let-7 miRNAs as key TLR7 signaling activators that serve to regulate the diverse functions of microglia in health and glioma. : Buonfiglioli et al. elucidate the role of let-7 miRNAs acting as Toll-like receptor (TLR) ligands in the brain. Select let-7 miRNAs function as signaling molecules to modulate diverse microglial functions and glioma growth through TLR7. These data establish let-7 miRNAs as TLR7 signaling activators of microglia in health and glioma. Keywords: glioblastoma, lethal-7, microglia, microRNA, Toll-like receptor 7

Immune escape is one of the hallmarks of cancer and several new treatment approaches attempt to modulate and restore the immune system’s capability to target cancer cells. At the heart of the immune recognition process lies antigen presentation from somatic mutations. These neo-epitopes are emerging as attractive targets for cancer immunotherapy and new strategies for rapid identification of relevant candidates have become a priority. We carefully screen TCGA data sets for recurrent somatic amino acid exchanges and apply MHC class I binding predictions. We propose a method for in silico selection and prioritization of candidates which have a high potential for neo-antigen generation and are likely to appear in multiple patients. While the percentage of patients carrying a specific neo-epitope and HLA-type combination is relatively small, the sheer number of new patients leads to surprisingly high reoccurence numbers. We identify 769 epitopes which are expected to occur in 77629 patients per year. While our candidate list will definitely contain false positives, the results provide an objective order for wet-lab testing of reusable neo-epitopes. Thus recurrent neo-epitopes may be suitable to supplement existing personalized T cell treatment approaches with precision treatment options.

Success of adoptive T cell therapy (ATT) is dependent on sufficient numbers of T cells and the characteristics of the final T cell product. In several studies, clinical grade CD19 CAR T cell products could not be generated from about 6-30% patients, particularly if they were isolated from older or heavily pretreated diffuse large B cell lymphoma (DLBCL) patients. In cyclophosphamide/fludarabine-lymphodepleted patients with persistent or progressive disease a sequential second dose of T cells has been shown to be effective resulting in tumor regression. Here we investigated to what extend T cell numbers could be increased via prolonged expansion with standard cytokines IL-7/IL-15 and how transcriptome and function of central memory T cells (Tcm) longitudinally change during culture. Method: Murine and human T cells were cultured with the cytokine combination IL-7/IL-15. Short-term expanded (ST, one week) and long-term expanded (LT) CD8+ (4 weeks) and CD4+ (3 weeks) T cells were compared for proliferation capacity (CFSE), extent of apoptosis (AnnexinV), up-regulation of T cell inhibitory receptors (TIRs) and cytokine expression pattern after in vitro re-stimulation upon anti-CD3/CD28 stimulation. Further, RNA sequencing of ST and LT expanded murine CD8+ and CD4+ Tcm followed by unsupervised hierarchical clustering, principal component analysis (PCA) and differential expression analysis was performed. In vivo mouse models were used to analyze engraftment, persistence and anti-tumor capacity applying our bioluminescent dual-luciferase reporter mouse (BLITC - bioluminescent imaging of T cells) allowing us to monitor migration, expansion (RLuc luciferase) and activation (NFAT-driven Click-beetle luciferase) of adoptively transferred T cells in vivo. Finally, we analyzed the expansion and in vitro properties of T cells from healthy donors and DLBCL patients. Results: There was a 50-fold increase of T cells in LT vs. ST culture, the Tcmproportion was extended and stem cell markers were comparable or even higher expressed in LT expanded T cells. Differential analysis revealed 2786 (CD8) and 912 (CD4) with statistically significant expression alterations with generally only moderate effect size when comparing LT and ST expanded T cells. Interestingly, the dynamically modified genes largely overlapped for CD8 and CD4 T cells suggesting culture-associated changes. Comparable RLuc signals and T cells counts in peripheral lymph nodes (LN) and spleen indicate similar engraftment (4 weeks post ATT) and persistence capacities (up to 6 months post ATT) of transferred ST and LT T cells. SV40-TAg+ tumor bearing mice were treated with TCR-I retrovirally transduced CD8+ BLITC T cells, which were ST or LT expanded. The T cells infiltrated rapidly in the tumor where they got similarly activated resulting in a complete tumor rejection in all recipient mice. Finally, we analyzed the expansion and in vitro properties of T cells from healthy donors (n=3-5) and DLBCL patients (n=3) who were eligible for CAR T cell therapy. LT T cell expansion from healthy donors resulted in a 10.000-fold increase of CD8+CD45RO+CCR7+ T cells. In vitro assays showed comparable apoptosis and expression of TIRs between ST and LT CD8 T cells and stable expression of IFN-g and TNF-a within the first 3 weeks. The CD8+CD45RO+CCR7+ T cell expansion from DLBCL patients was weaker in comparison to healthy donors. The extent of cell death and up-regulation of TIRs after re-stimulation was comparable between ST and LT T cells, whereas cytokine expression varied individually. Conclusion: Our data suggest that it is feasible to expand CD8+ and CD4+ murine and human T cells up to a month, thereby increasing numbers of T cells with Tcm/Tscm properties and with sustained function for murine and human T cells from healthy donors, whereas there seems to be a high individual variance for DLBCL patients, which warrants further investigation in larger patient cohorts. Disclosures Bullinger: Bayer: Other: Financing of scientific research; Abbvie: Honoraria; Seattle Genetics: Honoraria; Sanofi: Honoraria; Pfizer: Honoraria; Novartis: Honoraria; Menarini: Honoraria; Jazz Pharmaceuticals: Honoraria; Janssen: Honoraria; Hexal: Honoraria; Gilead: Honoraria; Daiichi Sankyo: Honoraria; Celgene: Honoraria; Bristol-Myers Squibb: Honoraria; Astellas: Honoraria; Amgen: Honoraria.

Genetic heterogeneity between and within tumours is a major factor determining cancer progression and therapy response. Here we examined DNA sequence and DNA copy-number heterogeneity in colorectal cancer (CRC) by targeted high-depth sequencing of 100 most frequently altered genes. In 97 samples, with primary tumours and matched metastases from 27 patients, we observe inter-tumour concordance for coding mutations; in contrast, gene copy numbers are highly discordant between primary tumours and metastases as validated by fluorescent in situ hybridization. To further investigate intra-tumour heterogeneity, we dissected a single tumour into 68 spatially defined samples and sequenced them separately. We identify evenly distributed coding mutations in APC and TP53 in all tumour areas, yet highly variable gene copy numbers in numerous genes. 3D morpho-molecular reconstruction reveals two clusters with divergent copy number aberrations along the proximal–distal axis indicating that DNA copy number variations are a major source of tumour heterogeneity in CRC., The contribution of intra-tumour heterogeneity is increasingly associated with resistance to therapy. Here, the authors use genomic analyses to study heterogeneity in colorectal cancer and perform in-depth reconstruction of heterogeneity in one sample.

e17577 Background: Salivary gland tumors (SGT) represent a rare and heterogeneous group of malignancies. No standard treatment exists in the advanced situation and the prognosis is poor. We here report characteristics and clinical outcomes of patients with SGT discussed at the Charité molecular tumor board (MTB). Methods: Patients with advanced cancer and no curative treatment option were discussed at the Charité MTB. Eligible patients underwent fresh tissue sampling and subsequent whole exome (WES) and RNA sequencing (RNA-seq) and immunohistochemical analyses (EGFR, HER2, AR as well as validation tests) or panel sequencing. Results from molecular testing were discussed at the MTB and patients were followed-up after recommendations were made. Results: 24 patients (median age 56 years, 13 male, 11 female) with advanced SGT were presented at the MTB between 2016 and 2019 (9 adenoidcystic carcinomas, 5 adenocarcinomas, 3 mucoepidermoid, 2 carcinosarcoma, 5 miscellaneous). WES/RNA sequencing was performed on tumor tissue from 16 patients. 2 patients were not included in the sequencing program and WES/RNA-Seq was ongoing for another 4 patients at the time of analysis. For another 2 patients, panel sequencing and IHC analysis, respectively was done. Results from analyses were discussed and a median of 2 recommendations, ranked by priority according to prespecified evidence levels, were made for 17 patients, each. Most commonly proposed treatment options by the MTB were FGFR inhibitors in 6 patients, mTOR or PARP inhibitors in 5 each, EGFR, HDAC inhibitors or antiandrogen therapy in 4, each. Treatments following MTB recommendations were initiated in 8 patients, 1 of which received a second recommended therapy after progression (antiandrogen therapy in 4, EGFR inhibitor in 2, a PDGFR, mTOR and PARP inhibitor in 1, each). A clinical benefit (CR = 1; Mixed Response = 1, SD = 3) was achieved in 5 patients, including a complete response in a patient with a metastatic adenocarcinoma of the parotid gland, treated with antiandrogen therapy. Conclusions: Precision oncology represents a feasible treatment strategy in patients with advanced SGT and shows early evidence of activity in a subset of patients. These results suggest further exploration of personalized therapy in these hard-to-treat tumors.

e24164Background: Precision Oncology programs hold promise to improve the treatment of cancer patients. The interpretation and prioritization of complex molecular data from comprehensive analyses h...

e14613 Background: Immune checkpoints are an emerging treatment target in head and neck squamous cell carcinoma (HNSCC). Expression of PD-L1 and an IFNG immune signature have been shown as biomarkers of response. In this study we analyzed mutational signatures to identify recurrent mutational patterns associated with inflammation. Methods: HNSCC mutation and gene expression data were downloaded (n = 496, TCGA). Inflamed tumors were identified through upregulation of a predefined 6-gene IFNG immune signature. Mutational load, base exchange motifs and a BRCAness signature were analyzed in inflamed and non-inflamed tumors. Results were validated in independent datasets of cervical, urothelial and lung cancer (TCGA). Results: Total mutational load did not correlate with tumor inflammation (r = -0.03, p = 0.5). An APOBEC-associated tCw (thymine – cytosine – adenine/thymine) mutational signature was significantly associated with inflammation (r = 0.26, p = 2.923e-09). The tCw signature was furthermore correlated with the expression of PD-L1 and other immune checkpoints (r = 0.19, p = 1.723e-05). The TCW mutational signature correlated with the expression of APOBEC3 genes. Expression of APOBEC3 genes also correlated with tumor inflammation (r = 0.62, p < 2.2e-16). As a second mutational signature, indels and an independent BRCAness signature were significantly enriched in non-inflamed tumors (p = 6.464e-14). Enrichment of an APOBEC mutational signature in inflamed tumors could be validated in cervical and urothelial carcinoma but not NSCLC. Conclusions: In HNSCC, overall mutational load is not associated with inflammation. BRCAness is significantly associated with immune-desertion whereas expression of APOBEC genes and an APOBEC mutational signature significantly correlates with the expression of PD-L1 and a T-cell inflamed signature. These findings suggest that a specific mutational pattern might serve as a biomarker for immune checkpoint inhibition in cancer.

Motivation: Even though a number of genome projects have been finished on the sequence level, still only a small proportion of DNA regulatory elements have been identified. Growing amounts of gene expression data provide the possibility of finding coregulated genes by clustering methods. By analysis of the promoter regions of those genes, rather weak signals of transcription factor binding sites may be detected. Results: We introduce the new algorithm ITB, an Integrated Tool for Box finding, which combines frequency and positional information to predict transcription factor binding sites in upstream regions of coregulated genes. Motifs are extracted by exhaustive analysis of regular expression-like patterns and by estimating probabilities of positional clusters of motifs. ITB detects consensus sequences of experimentally verified transcription factor binding sites of the yeast Saccharomyces cerevisiae. Moreover, a number of new binding site candidates with significant scores are predicted. Besides applying ITB on yeast upstream regions, the program is run on human promoter sequences. Availability: ITB is available upon request. Contact: s.kielbasa@itb.biologie.hu-berlin.de * Both authors contributed equally.

Multiple-shock experiments with fluid hydrogen have shown that a transition from semi-conducting behaviour to metal-like conductivity occurs at pressures of about 100 GPa. We apply an equation of state developed recently to determine Hugoniots and isentropes in dense hydrogen and deuterium plasma in the regions of partial dissociation and partial ionization.

We combine equations of state valid for the dense, neutral fluid and the dense, fully ionized plasma to obtain an equation of state for the intermediate region where partial dissociation and ionization occur. A region of thermodynamic instability is found which is known as plasma phase transition. The corresponding coexistence region and the coexistence line are derived. As a first application of the new equation of state, Hugoniot curves are calculated and compared with experiments and other theories.

We combine equations of state valid for the dense, neutral fluid and the dense, fully ionized plasma to obtain a new equation of state for the intermediate region where partial dissociation and ionization occur. A region of thermodynamic instability is found which is known as plasma phase transition. Hugoniots curves are calculated and compared with experiments and other theories.

The search for low autocorrelated binary sequences is a classical example of a discrete frustrated optimization problem. We demonstrate the efficiency of a class of evolutionary algorithms to tackle the problem. A suitable mutation operator using a preselection scheme is constructed, and the optimal parameters of the strategy are determined.

We consider the adiabatic equation of state for partially ionized non-ideal plasma. Plasma isentropes are calculated with the Pade technique in the chemical picture. The interplay of ionization/dissociation equilibrium and non-ideality is investigated.

Background Diabetes like many diseases and biological processes is not mono-causal. On the one hand multi-factorial studies with complex experimental design are required for its comprehensive analysis. On the other hand, the data from these studies often include a substantial amount of redundancy such as proteins that are typically represented by a multitude of peptides. Coping simultaneously with both complexities (experimental and technological) makes data analysis a challenge for Bioinformatics. Results We present a comprehensive work-flow tailored for analyzing complex data including data from multi-factorial studies. The developed approach aims at revealing effects caused by a distinct combination of experimental factors, in our case genotype and diet. Applying the developed work-flow to the analysis of an established polygenic mouse model for diet-induced type 2 diabetes, we found peptides with significant fold changes exclusively for the combination of a particular strain and diet. Exploitation of redundancy enables the visualization of peptide correlation and provides a natural way of feature selection for classification and prediction. Classification based on the features selected using our approach performs similar to classifications based on more complex feature selection methods. Conclusions The combination of ANOVA and redundancy exploitation allows for identification of biomarker candidates in multi-dimensional MALDI-TOF MS profiling studies with complex experimental design. With respect to feature selection our method provides a fast and intuitive alternative to global optimization strategies with comparable performance. The method is implemented in R and the scripts are available by contacting the corresponding author.

Systems biologists often have to deal with large gene groups obtained from high-throughput experiments, genome-wide predictions, and literature searches. Handling and functional interpretation of these gene groups is rather challenging. Problems arise from redundancies in databases, where a gene is given several names or identifiers, and from falsely assigned genes in the list. Moreover, genes in gene groups obtained by different methods are often represented by different types of identifiers, or are even genes from other model organisms. Thus, research in systems biology requires software tools that help to handle and interpret gene groups.

Increasingly used high throughput experimental techniques, like DNA or protein microarrays give as a result groups of interesting, e.g. differentially regulated genes which require further biological interpretation. With the systematic functional annotation provided by the Gene Ontology the information required to automate the interpretation task is now accessible. However, the determination of statistical significance of a biological process within these groups is still an open question. In answering this question, multiple testing issues must be taken into account to avoid misleading results. Here we present a statistical framework that tests whether functions, processes or locations described in the Gene Ontology are significantly enriched within a group of interesting genes when compared to a reference group. First we define an exact analytical expression for the expected number of false positives that allows us to calculate adjusted p-values to control the false discovery rate. Next, we demonstrate and discuss the capabilities of our approach using publicly available microarray data on cell-cycle regulated genes. Further, we analyze the robustness of our framework with respect to the exact gene group composition and compare the performance with earlier approaches. The software package GOSSIP implements our method and is made freely available at http://gossip.gene-groups.net/.

Host cell reactions are a crucial determinant for tumor invasion. We analyzed on a genomewide scale gene expression differences between microdissected tissues taken from unaffected liver tissue of a human colorectal tumor (LS174) growing in the livers of nude mice and tissue from the host part of the invasive front. Due to the low degree of interspecies cross-hybridization of 15% as determined on Affymetrix microarrays, our xenograft model allowed for the distinction of genes of murine versus human origin even if the respective tissues could not be isolated separately. Using the gene ontology (GO) classification, we were able to determine patterns of up- and downregulated genes in the liver part of the invasive front. We observed a pronounced overrepresentation, e.g., of the GO terms “extracellular matrix,” “cell communication,” “response to biotic stimulus,” “structural molecule activity” and “cell growth,” indicating a very pronounced host cell response to tumor invasion. On the single gene level, hepatic stellate cell (HSC) activation markers were overrepresented in the liver part of the invasion front. Immunohistochemistry and qPCR confirmed an activation of HSC as well as an increased number of HSC in the invasive front as compared to the noninvaded liver tissue. In summary, our data demonstrate the feasibility of an interspecies differential gene expression approach on a genomewide scale. © 2005 Wiley-Liss, Inc.

It is known since the fifties that discharges between two electrodes bridged by an insulator in high vacuum start in flashing over the insulating surface. A so-called sliding spark develops. Bridging the electrodes by a capillary, the same phenomenon was observed. The capillaries were typically made of polyethylene in order to observe line-free recombination spectra of C V I. During the discharge the capillary wall material is evaporated and ionized due to Joule heating and a hot dense carbon–hydrogen plasma is formed. In high-vacuum discharges the capillary is filled in much less than 50 ns. Typical plasma parameters are for electron density and for electron temperature. Since the sixties capillary discharge experiments were of interest as highly reproducible light sources. Sparks emitting intense continuum radiation in the visible and ultraviolet spectral region are important for many applications: temperature determination in plasma by means of line-reversal method, for measurement of absorption coefficients in the ultraviolet and soft X-ray domains, especially of the discontinuities at the absorption edges, or for use as radiation standards. Today they are considered as promising x-ray laser sources. Electron density and temperature in the plasma column (Fig. 1) are determined by measurement of emitted absolute radiation intensity from optical thin and optical thick layers. As the process of ablation continues more and more material is released from the wall of the capillary and transformed into plasma. The increase in plasma density is accompanied by a steady decrease in temperature in the way that the pressure remains almost constant. Radiation from prominent bound-bound transitions allows to record the temporal appearance of ions of different charges. At the temperatures under consideration hydrogen is fully ionized. The carbon ions may be identified by the line radiation from the transitions between the lowest excited states and the ground states, respectively. The experimental data of Fig. 2 suggest that the plasma composition in the first hundreds of nanoseconds is dominated by C VI and C v. The massive appearance of highly charged carbon ions is still not well understood.

Multiple-shock experiments with fluid hydrogen have shown that a transition from semiconducting behavior to metal-like conductivity occurs at pressures (p) of about 140 GPa and temperatures (T) near 3000 K. We model the p-T pathway by Hugoniot curves (initial shock) and isentropes (subsequent shocks). For the calculation of these curves we apply an expression for the free energy developed recently for dense hydrogen and deuterium plasma in the regions of partial dissociation and partial ionization. Furthermore, we discuss the relations between Hugoniot curves, isentropes and the coexistence line of the plasma phase transition.

For analysis and supervision of machining processes it is desirable to select a small set of parameter that are suitable to characterize the process. In order to reduce the number of characteristic process parameter one should use nonlinear or linear analysis methods whichever are more appropriate. Detailed analysis on the basis of prediction models and deterministic versus stochastic plots can thus help to develop and select successful monitoring and control strategies. Therefore, investigations on cutting processes with methods of nonlinear time series analysis are made under two aspects. The first aspect is to find out, if nonlinear dynamics components are an essential part of the process. The second aim is to condense and reinforce information that describes the state of the process and the tools used. Measurement signals taken from turning and milling processes are then analyzed under these aspects. The methods described have already proven to be useful for monitoring tasks.

High-density DNA arrays allow measurements of gene expression levels (messenger RNA abundance) for thousands of genes simultaneously. We analyze arrays with spotted cDNA used in monitoring of expression profiles. A dilution series of a mouse liver probe is deployed to quantify the reproducibility of expression measurements. Saturation effects limit the accessible signal range at high intensities. Additive noise and outshining from neighboring spots dominate at low intensities. For repeated measurements on the same filter and filter-to-filter comparisons correlation coefficients of 0.98 are found. Next we consider the clustering of gene expression time series from stimulated human fibroblasts which aims at finding co-regulated genes. We analyze how preprocessing, the distance measure, and the clustering algorithm affect the resulting clusters. Finally we discuss algorithms for the identification of transcription factor binding sites from clusters of co-regulated genes. (c) 2001 American Institute of Physics.

3082 Background: KEAP1 and STK11 mutations are associated with resistance to immune checkpoint inhibition (ICI) in non-small cell lung cancer (NSCLC). Mechanisms are currently unknown. Methods: We examined mutation, methylation, copy number and gene expression data from the cancer genome atlas (TCGA) lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LSCC), head and neck squamous cell carcinoma (HNSCC) and cervical carcinoma (CESC) data sets as well as public single cell gene expression data from a HNSCC cohort. Pathway annotations were performed using gene set enrichment analysis. A previously published cohort of NSCLC patients treated with ICI was analyzed for the predictive value of NFE2L2 mutations on PFS. Results: Annotation of STK11 and KEAP1 mutant LUAD revealed identical gene set enrichment for mitochondrial metabolism and downregulation of the STING-pathway, immune checkpoints, and interferon signaling. A STK11/KEAP1-mutation derived gene expression signature was established in LUAD and found to be driven by NFE2L2-regulated genes. This gene expression signature was independently predictive of immune desertion in LSCC, CESC and HNSCC and associated with STING-pathway downregulation in single cell sequencing analyses in HNSCC. KEAP1 and STK11 mutations were less frequent in LSCC, CESC and HNSCC but NFE2L2 mutations were identified in 15, 6 and 5%, respectively. NFE2L2 mutant SCC exhibited upregulation of the 15-gene- signature as well as immune desertion. In NSCLC, NFE2L2 mutations were associated with significantly worse PFS with ICI. Conclusions: Alterations of KEAP1, STK11, NFE2L2 and other related genes are linked to NFE2L2 target gene upregulation and immune desertion in LUAD, CESC, LSCC and HNSCC alike. The NFE2L2 pathway should be investigated clinically as a putative negative predictive biomarker for ICI and a potential therapeutic target.

Multiple Arabidopsis thaliana clones from an experimental series of cDNA microarrays are evaluated in order to identify essential sources of noise in the spotting and hybridization process. Theoretical and experimental strategies for an improved quantitative evaluation of cDNA microarrays are proposed and tested on a series of differently diluted control clones. Several sources of noise are identified from the data. Systematic and stochastic fluctuations in the spotting process are reduced by control spots and statistical techniques. The reliability of slide to slide comparison is critically assessed within the statistical framework of pattern matching and classification.

The time evolution of the population of excited atomic and ionic levels for an ensemble of reacting particles in dense plasmas is studied on the basis of a master equation. Many-body effects taken into account via energy-level shifts that are determined by the interaction parts of the chemical potentials of free and bound particles. These chemical potentials are calculated from an approximation for free partially ionized plasmas accounting for exchange and correlation as well as for short-range repulsion due to bound shell electrons. Using semi-empirical cross sections the method is applied to investigate the recombination of dense plasma containing carbon and hydrogen. The master equation can be combined with a temperature equation to account for different thermodynamic constraints. We compare the isentropic, isothermal, and isoenergetic recombination of dense hydrogen plasma.

Recent shock-wave experiments on fluid hydrogen have shown that a transition from nonconducting to metallic-like conductivity occurs at Mbar pressures. On the other hand, a transition from metallic to non-metallic conductivities has been observed in aluminum and copper plasmas at about 0.1 solid state density using the rapid wire evaporation technique. The equation of state and composition of both shock-compressed hydrogen and expanded metals are calculated within a partially ionized plasma model. The conductivity is determined in linear response theory taking into account all relevant scattering processes of free electrons on T matrix level. Reasonable agreement with the experiments is found.