Auf der Suche nach der nationalen Innovationskultur Deutschlands - die Etablierung der Verfahrenstechnik in der BRD, DDR seit 1950

Die Rolle der Hochschulen im Innovationssystem sowohl der BRD als auch der DDR hat sich in den letzten fünfzig Jahren zum Teil dramatisch geändert. Der Veränderungsprozess in der Bundesrepublik lässt sich grob in drei Phasen einteilen, die sich zwar überlappen, dennoch im wesentlichen eine zeitliche Abfolge darstellen. 1) Grundlagenorientierung und Anwendungsferne (1940er und 1950er Jahre), 2) Berufsausbildungsfunktion (1960er), 3) Wirtschaftsorientierung (1970er bis heute). Die große Drittmittel- und Wirtschaftsorientierung allein, die es in ähnlicher Form auch in der DDR gegeben hat, garantiert allerdings noch keinen Erfolg des Innovationssystems. Die vorliegende Studie untersucht den Disziplinbildungsprozess in der Verfahrenstechnik an ost- und westdeutschen Hochschulen - speziell geht es um die Frage, inwieweit die beiden politischen Systeme zu einer differenzierten Ausrichtung der Disziplin und zu unterschiedlichem Innovationsverhalten geführt haben könnten. Durch den methodisch-theoretischen Zugang der Kollektivbiographie zeigt sich, dass die unterschiedlichen Reaktions- und Verhaltensmuster der wissenschaftlich-technischen Eliten in Ost- und Westdeutschland den Disziplinbildungsprozess in verschiedene Richtungen vorantreiben. -- The role of universities in the system of innovation changed dramatically in the last fifty years. This observation is evident from the analysis of (examples in) the German Democratic Republic (GDR) and the Federal Republic of Germany (FRG). The change in the FRG can be structured in three phases: 1) Orientation towards basic science and neglection of applications (1940´s and 1950´s) 2) Orientation towards the educational function of universities for professional careers (1960´s) 3) Orientation towards industry and business (1970´s onwards) The orientation towards industry and business existed in similar form in the GDR but did not guarantee the success of the system of innovation. This study examines the process of discipline establishment in Verfahrenstechnik (chemical engineering) at east and west German universities. Specifically, the following question is posed: To what degree did the two political systems lead to a different approach of the disciplines towards innovation. Employing the method of collective biography this study demonstrates that the scientific elites in east and west Germany developed their respective disciplines differently.Management von technischen Innovationen und Forschung und Entwicklung,Wirtschaftsgeschichte,Bildung,management of technological innovation and R&D,economic history,education

Mental Health Conditions Across 300 Popular Films: A Research Update from 2016 to 2022

This report examines the prevalence and portrayals of mental health conditions across the 100 top-grossing films from 2022, comparing the new findings to the Initiative's previous studies covering 2016 and 2019

Integral and peripheral association of proteins and protein complexes with Yersinia pestis inner and outer membranes

Yersinia pestis proteins were sequentially extracted from crude membranes with a high salt buffer (2.5 M NaBr), an alkaline solution (180 mM Na2CO3, pH 11.3) and membrane denaturants (8 M urea, 2 M thiourea and 1% amidosulfobetaine-14). Separation of proteins by 2D gel electrophoresis was followed by identification of more than 600 gene products by MS. Data from differential 2D gel display experiments, comparing protein abundances in cytoplasmic, periplasmic and all three membrane fractions, were used to assign proteins found in the membrane fractions to three protein categories: (i) integral membrane proteins and peripheral membrane proteins with low solubility in aqueous solutions (220 entries); (ii) peripheral membrane proteins with moderate to high solubility in aqueous solutions (127 entries); (iii) cytoplasmic or ribosomal membrane-contaminating proteins (80 entries). Thirty-one proteins were experimentally associated with the outer membrane (OM). Circa 50 proteins thought to be part of membrane-localized, multi-subunit complexes were identified in high Mr fractions of membrane extracts via size exclusion chromatography. This data supported biologically meaningful assignments of many proteins to the membrane periphery. Since only 32 inner membrane (IM) proteins with two or more predicted transmembrane domains (TMDs) were profiled in 2D gels, we resorted to a proteomic analysis by 2D-LC-MS/MS. Ninety-four additional IM proteins with two or more TMDs were identified. The total number of proteins associated with Y. pestis membranes increased to 456 and included representatives of all six β-barrel OM protein families and 25 distinct IM transporter families

GeMMA: functional subfamily classification within superfamilies of predicted protein structural domains

GeMMA (Genome Modelling and Model Annotation) is a new approach to automatic functional subfamily classification within families and superfamilies of protein sequences. A major advantage of GeMMA is its ability to subclassify very large and diverse superfamilies with tens of thousands of members, without the need for an initial multiple sequence alignment. Its performance is shown to be comparable to the established high-performance method SCI-PHY. GeMMA follows an agglomerative clustering protocol that uses existing software for sensitive and accurate multiple sequence alignment and profile–profile comparison. The produced subfamilies are shown to be equivalent in quality whether whole protein sequences are used or just the sequences of component predicted structural domains. A faster, heuristic version of GeMMA that also uses distributed computing is shown to maintain the performance levels of the original implementation. The use of GeMMA to increase the functional annotation coverage of functionally diverse Pfam families is demonstrated. It is further shown how GeMMA clusters can help to predict the impact of experimentally determining a protein domain structure on comparative protein modelling coverage, in the context of structural genomics

Structural genomics is the largest contributor of novel structural leverage

The Protein Structural Initiative (PSI) at the US National Institutes of Health (NIH) is funding four large-scale centers for structural genomics (SG). These centers systematically target many large families without structural coverage, as well as very large families with inadequate structural coverage. Here, we report a few simple metrics that demonstrate how successfully these efforts optimize structural coverage: while the PSI-2 (2005-now) contributed more than 8% of all structures deposited into the PDB, it contributed over 20% of all novel structures (i.e. structures for protein sequences with no structural representative in the PDB on the date of deposition). The structural coverage of the protein universe represented by today’s UniProt (v12.8) has increased linearly from 1992 to 2008; structural genomics has contributed significantly to the maintenance of this growth rate. Success in increasing novel leverage (defined in Liu et al. in Nat Biotechnol 25:849–851, 2007) has resulted from systematic targeting of large families. PSI’s per structure contribution to novel leverage was over 4-fold higher than that for non-PSI structural biology efforts during the past 8 years. If the success of the PSI continues, it may just take another ~15 years to cover most sequences in the current UniProt database

The APEX Quantitative Proteomics Tool: Generating protein quantitation estimates from LC-MS/MS proteomics results

Mass spectrometry (MS) based label-free protein quantitation has mainly focused on analysis of ion peak heights and peptide spectral counts. Most analyses of tandem mass spectrometry (MS/MS) data begin with an enzymatic digestion of a complex protein mixture to generate smaller peptides that can be separated and identified by an MS/MS instrument. Peptide spectral counting techniques attempt to quantify protein abundance by counting the number of detected tryptic peptides and their corresponding MS spectra. However, spectral counting is confounded by the fact that peptide physicochemical properties severely affect MS detection resulting in each peptide having a different detection probability. Lu et al. (2007) described a modified spectral counting technique, Absolute Protein Expression (APEX), which improves on basic spectral counting methods by including a correction factor for each protein (called O(i) value) that accounts for variable peptide detection by MS techniques. The technique uses machine learning classification to derive peptide detection probabilities that are used to predict the number of tryptic peptides expected to be detected for one molecule of a particular protein (O(i)). This predicted spectral count is compared to the protein's observed MS total spectral count during APEX computation of protein abundances. Results: The APEX Quantitative Proteomics Tool, introduced here, is a free open source Java application that supports the APEX protein quantitation technique. The APEX tool uses data from standard tandem mass spectrometry proteomics experiments and provides computational support for APEX protein abundance quantitation through a set of graphical user interfaces that partition thparameter controls for the various processing tasks. The tool also provides a Z-score analysis for identification of significant differential protein expression, a utility to assess APEX classifier performance via cross validation, and a utility to merge multiple APEX results into a standardized format in preparation for further statistical analysis. Conclusion: The APEX Quantitative Proteomics Tool provides a simple means to quickly derive hundreds to thousands of protein abundance values from standard liquid chromatography-tandem mass spectrometry proteomics datasets. The APEX tool provides a straightforward intuitive interface design overlaying a highly customizable computational workflow to produce protein abundance values from LC-MS/MS datasets.National Institute of Allergy and Infectious Diseases (NIAID) N01-AI15447National Institutes of HealthNational Science Foundation, the Welsh and Packard FoundationsInternational Human Frontier Science ProgramCenter for Systems and Synthetic Biolog

The implementation of the serial trial intervention for pain and challenging behaviour in advanced dementia patients (STA OP!): a clustered randomized controlled trial

<p>Abstract</p> <p>Background</p> <p>Pain (physical discomfort) and challenging behaviour are highly prevalent in nursing home residents with dementia: at any given time 45-80% of nursing home residents are in pain and up to 80% have challenging behaviour. In the USA Christine Kovach developed the serial trial intervention (STI) and established that this protocol leads to less discomfort and fewer behavioural symptoms in moderate to severe dementia patients. The present study will provide insight into the effects of implementation of the Dutch version of the STI-protocol (STA OP!) in comparison with a control intervention, not only on behavioural symptoms, but also on pain, depression, and quality of life. This article outlines the study protocol.</p> <p>Methods/Design</p> <p>The study is a cluster randomized controlled trial in 168 older people (aged >65 years) with mild or moderate dementia living in nursing homes. The clusters, Dutch nursing homes, are randomly assigned to either the intervention condition (training and implementation of the STA OP!-protocol) or the control condition (general training focusing on challenging behaviour and pain, but without the step-wise approach). Measurements take place at baseline, after 3 months (end of the STA OP! training period) and after 6 months.</p> <p>Primary outcome measures are symptoms of challenging behaviour (measured with the Cohen-Mansfield Agitation Inventory (CMAI) and the Neuropsychiatric Inventory-Nursing Home version (NPI-NH)), and pain (measure with the Dutch version of the Pain Assessment Checklist for Seniors (PACSLAC-D) and the Minimum Data Set of the Resident Assessment Instrument (MDS-RAI) pain scale). Secondary outcome measures include symptoms of depression (Cornell and MDS-RAI depression scale), Quality of Live (Qualidem), changes in prescriptions of analgesics and psychotropic drugs, and the use of non-pharmacological comfort interventions (e.g. snoezelen, reminiscence therapy).</p> <p>Discussion</p> <p>The transfer from the American design to the Dutch design involved several changes due to the different organisation of healthcare systems. Specific strengths and limitations of the study are discussed.</p> <p>Trial registration</p> <p>Netherlands Trial Register (NTR): <a href="http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=1967">NTR1967</a></p

Development and validation of a targeted gene sequencing panel for application to disparate cancers

Next generation sequencing has revolutionised genomic studies of cancer, having facilitated the development of precision oncology treatments based on a tumour’s molecular profile. We aimed to develop a targeted gene sequencing panel for application to disparate cancer types with particular focus on tumours of the head and neck, plus test for utility in liquid biopsy. The final panel designed through Roche/Nimblegen combined 451 cancer-associated genes (2.01 Mb target region). 136 patient DNA samples were collected for performance and application testing. Panel sensitivity and precision were measured using well-characterised DNA controls (n = 47), and specificity by Sanger sequencing of the Aryl Hydrocarbon Receptor Interacting Protein (AIP) gene in 89 patients. Assessment of liquid biopsy application employed a pool of synthetic circulating tumour DNA (ctDNA). Library preparation and sequencing were conducted on Illumina-based platforms prior to analysis with our accredited (ISO15189) bioinformatics pipeline. We achieved a mean coverage of 395x, with sensitivity and specificity of >99% and precision of >97%. Liquid biopsy revealed detection to 1.25% variant allele frequency. Application to head and neck tumours/cancers resulted in detection of mutations aligned to published databases. In conclusion, we have developed an analytically-validated panel for application to cancers of disparate types with utility in liquid biopsy

The FANCM:p.Arg658* truncating variant is associated with risk of triple-negative breast cancer

Abstract: Breast cancer is a common disease partially caused by genetic risk factors. Germline pathogenic variants in DNA repair genes BRCA1, BRCA2, PALB2, ATM, and CHEK2 are associated with breast cancer risk. FANCM, which encodes for a DNA translocase, has been proposed as a breast cancer predisposition gene, with greater effects for the ER-negative and triple-negative breast cancer (TNBC) subtypes. We tested the three recurrent protein-truncating variants FANCM:p.Arg658*, p.Gln1701*, and p.Arg1931* for association with breast cancer risk in 67,112 cases, 53,766 controls, and 26,662 carriers of pathogenic variants of BRCA1 or BRCA2. These three variants were also studied functionally by measuring survival and chromosome fragility in FANCM−/− patient-derived immortalized fibroblasts treated with diepoxybutane or olaparib. We observed that FANCM:p.Arg658* was associated with increased risk of ER-negative disease and TNBC (OR = 2.44, P = 0.034 and OR = 3.79; P = 0.009, respectively). In a country-restricted analysis, we confirmed the associations detected for FANCM:p.Arg658* and found that also FANCM:p.Arg1931* was associated with ER-negative breast cancer risk (OR = 1.96; P = 0.006). The functional results indicated that all three variants were deleterious affecting cell survival and chromosome stability with FANCM:p.Arg658* causing more severe phenotypes. In conclusion, we confirmed that the two rare FANCM deleterious variants p.Arg658* and p.Arg1931* are risk factors for ER-negative and TNBC subtypes. Overall our data suggest that the effect of truncating variants on breast cancer risk may depend on their position in the gene. Cell sensitivity to olaparib exposure, identifies a possible therapeutic option to treat FANCM-associated tumors