Consumer perceptions of co-branding alliances: Organizational dissimilarity signals and brand fit

This study explores how consumers evaluate co-branding alliances between dissimilar partner firms. Customers are well aware that different firms are behind a co-branded product and observe the partner firms’ characteristics. Drawing on signaling theory, we assert that consumers use organizational characteristics as signals in their assessment of brand fit and for their purchasing decisions. Some organizational signals are beyond the control of the co-branding partners or at least they cannot alter them on short notice. We use a quasi-experimental design and test how co-branding partner dissimilarity affects brand fit perception. The results show that co-branding partner dissimilarity in terms of firm size, industry scope, and country-of-origin image negatively affects brand fit perception. Firm age dissimilarity does not exert significant influence. Because brand fit generally fosters a benevolent consumer attitude towards a co-branding alliance, the findings suggest that high partner dissimilarity may reduce overall co-branding alliance performance

Bedrock geology of DFDP-2B, central Alpine Fault, New Zealand

<p>During the second phase of the Alpine Fault, Deep Fault Drilling Project (DFDP) in the Whataroa River, South Westland, New Zealand, bedrock was encountered in the DFDP-2B borehole from 238.5–893.2 m Measured Depth (MD). Continuous sampling and meso- to microscale characterisation of whole rock cuttings established that, in sequence, the borehole sampled amphibolite facies, Torlesse Composite Terrane-derived schists, protomylonites and mylonites, terminating 200–400 m above an Alpine Fault Principal Slip Zone (PSZ) with a maximum dip of 62°. The most diagnostic structural features of increasing PSZ proximity were the occurrence of shear bands and reduction in mean quartz grain sizes. A change in composition to greater mica:quartz + feldspar, most markedly below c. 700 m MD, is inferred to result from either heterogeneous sampling or a change in lithology related to alteration. Major oxide variations suggest the fault-proximal Alpine Fault alteration zone, as previously defined in DFDP-1 core, was not sampled.</p

Petrophysical, Geochemical, and Hydrological Evidence for Extensive Fracture-Mediated Fluid and Heat Transport in the Alpine Fault's Hanging-Wall Damage Zone

International audienceFault rock assemblages reflect interaction between deformation, stress, temperature, fluid, and chemical regimes on distinct spatial and temporal scales at various positions in the crust. Here we interpret measurements made in the hanging‐wall of the Alpine Fault during the second stage of the Deep Fault Drilling Project (DFDP‐2). We present observational evidence for extensive fracturing and high hanging‐wall hydraulic conductivity (∼10−9 to 10−7 m/s, corresponding to permeability of ∼10−16 to 10−14 m2) extending several hundred meters from the fault's principal slip zone. Mud losses, gas chemistry anomalies, and petrophysical data indicate that a subset of fractures intersected by the borehole are capable of transmitting fluid volumes of several cubic meters on time scales of hours. DFDP‐2 observations and other data suggest that this hydrogeologically active portion of the fault zone in the hanging‐wall is several kilometers wide in the uppermost crust. This finding is consistent with numerical models of earthquake rupture and off‐fault damage. We conclude that the mechanically and hydrogeologically active part of the Alpine Fault is a more dynamic and extensive feature than commonly described in models based on exhumed faults. We propose that the hydrogeologically active damage zone of the Alpine Fault and other large active faults in areas of high topographic relief can be subdivided into an inner zone in which damage is controlled principally by earthquake rupture processes and an outer zone in which damage reflects coseismic shaking, strain accumulation and release on interseismic timescales, and inherited fracturing related to exhumation

The ALT pathway generates telomere fusions that can be detected in the blood of cancer patients.

Telomere fusions (TFs) can trigger the accumulation of oncogenic alterations leading to malignant transformation and drug resistance. Despite their relevance in tumour evolution, our understanding of the patterns and consequences of TFs in human cancers remains limited. Here, we characterize the rates and spectrum of somatic TFs across >30 cancer types using whole-genome sequencing data. TFs are pervasive in human tumours with rates varying markedly across and within cancer types. In addition to end-to-end fusions, we find patterns of TFs that we mechanistically link to the activity of the alternative lengthening of telomeres (ALT) pathway. We show that TFs can be detected in the blood of cancer patients, which enables cancer detection with high specificity and sensitivity even for early-stage tumours and cancers of high unmet clinical need. Overall, we report a genomic footprint that enables characterization of the telomere maintenance mechanism of tumours and liquid biopsy analysis.F.M., C.S. and I.C.-C. thank EMBL and The Wellcome Trust for funding. Sequencing experiments were supported by Cancer Research UK award 30306 (I.C.-C.). I.F. was funded by grants from the Spanish Ministry of Science and Innovation (PID2019-110339RB-I00) and the Comunidad de Madrid (S2022/BMB-7245). The CNIC and CBM-SO are supported by the Ministerio de Ciencia, Innovación y Universidades and are Severo Ochoa Centers of Excellence (CEX2020-001041-S, CEX2021-001154-S). R.C., A.A. and C.C.F. acknowledge the support of Associação David Vaz, Bolsa João Lobo Antunes—GAPIC (iMM/ FMUL) and Millennium bcp. All authors thank the computational resources provided by the European Bioinformatics Institute (EMBLEBI). The authors acknowledge the patients who kindly provided the biological samples used for this research and the Biobanco-iMM CAML, which enabled the collection, processing, and storage of tumour and blood samples from glioblastoma patients. Some of the figures were created using BioRender.com.S

Protoplast-Esculin Assay as a New Method to Assay Plant Sucrose Transporters: Characterization of AtSUC6 and AtSUC7 Sucrose Uptake Activity in Arabidopsis Col-0 Ecotype

The best characterized function of sucrose transporters of the SUC family in plants is the uptake of sucrose into the phloem for long-distance transport of photoassimilates. This important step is usually performed by one specific SUC in every species. However, plants possess small families of several different SUCs which are less well understood. Here, we report on the characterization of AtSUC6 and AtSUC7, two members of the SUC family in Arabidopsis thaliana. Heterologous expression in yeast (Saccharomyces cerevisiae) revealed that AtSUC6Col-0 is a high-affinity H+-symporter that mediates the uptake of sucrose and maltose across the plasma membrane at exceptionally low pH values. Reporter gene analyses revealed a strong expression of AtSUC6Col-0 in reproductive tissues, where the protein product might contribute to sugar uptake into pollen tubes and synergid cells. A knockout of AtSUC6 did not interfere with vegetative development or reproduction, which points toward physiological redundancy of AtSUC6Col-0 with other sugar transporters. Reporter gene analyses showed that AtSUC7Col-0 is expressed in roots and pollen tubes and that this sink specific expression of AtSUC7Col-0 is regulated by intragenic regions. Transport activity of AtSUC7Col-0 could not be analyzed in baker’s yeast or Xenopus oocytes because the protein was not correctly targeted to the plasma membrane in both heterologous expression systems. Therefore, a novel approach to analyze sucrose transporters in planta was developed. Plasma membrane localized SUCs including AtSUC6Col-0 and also sucrose specific SWEETs were able to mediate transport of the fluorescent sucrose analog esculin in transformed mesophyll protoplasts. In contrast, AtSUC7Col-0 is not able to mediate esculin transport across the plasma membrane which implicates that AtSUC7Col-0 might be a non-functional pseudogene. The novel protoplast assay provides a useful tool for the quick and quantitative analysis of sucrose transporters in an in planta expression system

De novo detection of somatic mutations in high-throughput single-cell profiling data sets.

Funder: European Molecular Biology Laboratory (EMBL Heidelberg); doi: https://doi.org/10.13039/100013060Funder: Wellcome Trust (Wellcome); doi: https://doi.org/10.13039/100004440Funder: Harvard Medical School; doi: https://doi.org/10.13039/100006691Characterization of somatic mutations at single-cell resolution is essential to study cancer evolution, clonal mosaicism and cell plasticity. Here, we describe SComatic, an algorithm designed for the detection of somatic mutations in single-cell transcriptomic and ATAC-seq (assay for transposase-accessible chromatin sequence) data sets directly without requiring matched bulk or single-cell DNA sequencing data. SComatic distinguishes somatic mutations from polymorphisms, RNA-editing events and artefacts using filters and statistical tests parameterized on non-neoplastic samples. Using >2.6 million single cells from 688 single-cell RNA-seq (scRNA-seq) and single-cell ATAC-seq (scATAC-seq) data sets spanning cancer and non-neoplastic samples, we show that SComatic detects mutations in single cells accurately, even in differentiated cells from polyclonal tissues that are not amenable to mutation detection using existing methods. Validated against matched genome sequencing and scRNA-seq data, SComatic achieves F1 scores between 0.6 and 0.7 across diverse data sets, in comparison to 0.2-0.4 for the second-best performing method. In summary, SComatic permits de novo mutational signature analysis, and the study of clonal heterogeneity and mutational burdens at single-cell resolution

The COVID-19 Pandemic as an Opportunity and Challenge for Registries in Health Services Research: Lessons Learned from the Lean European Open Survey on SARS-CoV-2 Infected Patients (LEOSS)

Zusammenfassung Ziel der Studie Aus der durch das Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) bedingten Coronavirus-Krankheit-2019 (COVID-19) haben sich Chancen und Herausforderungen fur den Aufbau von Registern in der Versorgungsforschung ergeben. Diese sollen exemplarisch am aktuell gro ss ten sektorenubergreifenden Register mit einem detaillierten klinischen Datensatz zu mit SARS-CoV-2 infizierten Patient:innen in Deutschland, der Lean European Open Survey on SARS-CoV-2 Infected Patients (LEOSS), aufgezeigt werden. Methodik Ziele von LEOSS waren es, ein kollaboratives und integratives Register zur Erfassung von anonymen Daten aus der Versorgung zu schaffen und die Daten der Wissenschaft im Sinne eines Open Science Ansatzes rasch bereitzustellen. Alleiniges Einschlusskriterium war der virologische Nachweis von SARS-CoV-2. Schlusselstrategien waren die Reallokation der vorhandenen personellen und technischen Ressourcen, die fruhe und direkte Einbeziehung von Vertreter:innen des Datenschutzes und der Ethikkommissionen sowie die Entscheidung zu einem iterativen und agilen Entwicklungs- und Anpassungsprozess. Ergebnisse Getragen von den zahlreichen kollaborierenden Institutionen konnte ein transsektorales und internationales Netzwerk mit aktuell 133 aktiv rekrutierenden Standorten und 7227 dokumentierten Fallen aufgebaut werden (Stand 18.03.2021, ein Jahr seit Rekrutierungsstart von LEOSS). Die Nutzung der Daten wurde uber auf der Projektwebseite verfugbare Werkzeuge zur Datenexploration, wie auch uber die teilautomatisierte Bereitstellung von Datensatzen verschiedenen Umfangs, innerhalb kurzer Zeit ermoglicht. Es wurden 97 Antrage zur Datennutzung aus 27 Themengebieten begutachtet. Im Peer-Review-Verfahren wurden 9 Arbeiten in internationalen Fachzeitschriften veroffentlicht. Schlussfolgerung Mit LEOSS konnte in kurzester Zeit ein System zur Erfassung klinischer Verlaufsdaten zu COVID-19 in Deutschland etabliert werden. Auch wenn in anderen Projekten fur spezifische Fragestellungen weitaus gro ss ere Datenbestande durch direkten Zugriff auf Quellsysteme analysiert werden konnten, wurde durch den einheitlich gepflegten und technisch gepruften Dokumentationsstandard mit vielen fachspezifischen Details ein sehr gro ss er Datensatz mit wertvollen Alleinstellungsmerkmalen geschaffen. Aus den Erfahrungen von LEOSS konnen Implikationen fur die zukunftige Gestaltung von Registern und eine rasche Reaktion auf Pandemien abgeleitet werden. Abstract Objective The Coronavirus Disease-2019 (COVID-19) pandemic has brought opportunities and challenges, especially for health services research based on routine data. In this article we will demonstrate this by presenting lessons learned from establishing the currently largest registry in Germany providing a detailed clinical dataset on Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infected patients: the Lean European Open Survey on SARS-CoV-2 Infected Patients (LEOSS). Methods LEOSS is based on a collaborative and integrative research approach with anonymous recruitment and collection of routine data and the early provision of data in an open science context. The only requirement for inclusion was a SARS-CoV-2 infection confirmed by virological diagnosis. Crucial strategies to successfully realize the project included the dynamic reallocation of available staff and technical resources, an early and direct involvement of data protection experts and the ethics committee as well as the decision for an iterative and dynamic process of improvement and further development. Results Thanks to the commitment of numerous institutions, a transsectoral and transnational network of currently 133 actively recruiting sites with 7,227 documented cases could be established (status: 18.03.2021). Tools for data exploration on the project website, as well as the partially automated provision of datasets according to use cases with varying requirements, enabled us to utilize the data collected within a short period of time. Data use and access processes were carried out for 97 proposals assigned to 27 different research areas. So far, nine articles have been published in peer-reviewed international journals. Conclusion As a collaborative effort of the whole network, LEOSS developed into a large collection of clinical data on COVID-19 in Germany. Even though in other international projects, much larger data sets could be analysed to investigate specific research questions through direct access to source systems, the uniformly maintained and technically verified documentation standard with many discipline-specific details resulted in a large valuable data set with unique characteristics. The lessons learned while establishing LEOSS during the current pandemic have already created important implications for the design of future registries and for pandemic preparedness and response

Longitudinal monitoring of disease burden and response using ctDNA from dried blood spots in xenograft models.

Whole-genome sequencing (WGS) of circulating tumour DNA (ctDNA) is now a clinically important biomarker for predicting therapy response, disease burden and disease progression. However, the translation of ctDNA monitoring into vital preclinical PDX models has not been possible owing to low circulating blood volumes in small rodents. Here, we describe the longitudinal detection and monitoring of ctDNA from minute volumes of blood in PDX mice. We developed a xenograft Tumour Fraction (xTF) metric using shallow WGS of dried blood spots (DBS), and demonstrate its application to quantify disease burden, monitor treatment response and predict disease outcome in a preclinical study of PDX mice. Further, we show how our DBS-based ctDNA assay can be used to detect gene-specific copy number changes and examine the copy number landscape over time. Use of sequential DBS ctDNA assays could transform future trial designs in both mice and patients by enabling increased sampling and molecular monitoring