Collaborations on YouTube: From Unsupervised Detection to the Impact on Video and Channel Popularity

YouTube is one of the most popular platforms for streaming of user-generated video. Nowadays, professional YouTubers are organized in so called multi-channel networks (MCNs). These networks offer services such as brand deals, equipment, and strategic advice in exchange for a share of the YouTubers' revenue. A major strategy to gain more subscribers and, hence, revenue is collaborating with other YouTubers. Yet, collaborations on YouTube have not been studied in a detailed quantitative manner. This paper aims to close this gap with the following contributions. First, we collect a YouTube dataset covering video statistics over three months for 7,942 channels. Second, we design a framework for collaboration detection given a previously unknown number of persons featuring in YouTube videos. We denote this framework for the analysis of collaborations in YouTube videos using a Deep Neural Network (DNN) based approach as CATANA. Third, we analyze about 2.4 years of video content and use CATANA to answer research questions providing guidance for YouTubers and MCNs for efficient collaboration strategies. Thereby, we focus on (i) collaboration frequency and partner selectivity, (ii) the influence of MCNs on channel collaborations, (iii) collaborating channel types, and (iv) the impact of collaborations on video and channel popularity. Our results show that collaborations are in many cases significantly beneficial in terms of viewers and newly attracted subscribers for both collaborating channels, showing often more than 100% popularity growth compared with non-collaboration videos.Comment: 28 pages, 21 figure

PupilEXT: Flexible Open-Source Platform for High-Resolution Pupillometry in Vision Research

The human pupil behavior has gained increased attention due to the discovery of the intrinsically photosensitive retinal ganglion cells and the afferent pupil control path’s role as a biomarker for cognitive processes. Diameter changes in the range of 10–2 mm are of interest, requiring reliable and characterized measurement equipment to accurately detect neurocognitive effects on the pupil. Mostly commercial solutions are used as measurement devices in pupillometry which is associated with high investments. Moreover, commercial systems rely on closed software, restricting conclusions about the used pupil-tracking algorithms. Here, we developed an open-source pupillometry platform consisting of hardware and software competitive with high-end commercial stereo eye-tracking systems. Our goal was to make a professional remote pupil measurement pipeline for laboratory conditions accessible for everyone. This work’s core outcome is an integrated cross-platform (macOS, Windows and Linux) pupillometry software called PupilEXT, featuring a user-friendly graphical interface covering the relevant requirements of professional pupil response research. We offer a selection of six state-of-the-art open-source pupil detection algorithms (Starburst, Swirski, ExCuSe, ElSe, PuRe and PuReST) to perform the pupil measurement. A developed 120-fps pupillometry demo system was able to achieve a calibration accuracy of 0.003 mm and an averaged temporal pupil measurement detection accuracy of 0.0059 mm in stereo mode. The PupilEXT software has extended features in pupil detection, measurement validation, image acquisition, data acquisition, offline pupil measurement, camera calibration, stereo vision, data visualization and system independence, all combined in a single open-source interface, available at https://github.com/openPupil/Open-PupilEXT

PupilEXT: Flexible Open-Source Platform for High-Resolution Pupillometry in Vision Research

The human pupil behavior has gained increased attention due to the discovery of the intrinsically photosensitive retinal ganglion cells and the afferent pupil control path’s role as a biomarker for cognitive processes. Diameter changes in the range of 10⁻² mm are of interest, requiring reliable and characterized measurement equipment to accurately detect neurocognitive effects on the pupil. Mostly commercial solutions are used as measurement devices in pupillometry which is associated with high investments. Moreover, commercial systems rely on closed software, restricting conclusions about the used pupil-tracking algorithms. Here, we developed an open-source pupillometry platform consisting of hardware and software competitive with high-end commercial stereo eye-tracking systems. Our goal was to make a professional remote pupil measurement pipeline for laboratory conditions accessible for everyone. This work’s core outcome is an integrated cross-platform (macOS, Windows and Linux) pupillometry software called PupilEXT, featuring a user-friendly graphical interface covering the relevant requirements of professional pupil response research. We offer a selection of six state-of-the-art open-source pupil detection algorithms (Starburst, Swirski, ExCuSe, ElSe, PuRe and PuReST) to perform the pupil measurement. A developed 120-fps pupillometry demo system was able to achieve a calibration accuracy of 0.003 mm and an averaged temporal pupil measurement detection accuracy of 0.0059 mm in stereo mode. The PupilEXT software has extended features in pupil detection, measurement validation, image acquisition, data acquisition, offline pupil measurement, camera calibration, stereo vision, data visualization and system independence, all combined in a single open-source interface, available at https://github.com/openPupil/Open-PupilEXT

GMP-Compliant Manufacturing of TRUCKs: CAR T Cells targeting GD2 and Releasing Inducible IL-18

Chimeric antigen receptor (CAR)-engineered T cells can be highly effective in the treatment of hematological malignancies, but mostly fail in the treatment of solid tumors. Thus, approaches using 4th advanced CAR T cells secreting immunomodulatory cytokines upon CAR signaling, known as TRUCKs (“T cells redirected for universal cytokine-mediated killing”), are currently under investigation. Based on our previous development and validation of automated and closed processing for GMP-compliant manufacturing of CAR T cells, we here present the proof of feasibility for translation of this method to TRUCKs. We generated IL-18-secreting TRUCKs targeting the tumor antigen GD2 using the CliniMACS Prodigy® system using a recently described “all-in-one” lentiviral vector combining constitutive anti-GD2 CAR expression and inducible IL-18. Starting with 0.84 x 108 and 0.91 x 108 T cells after enrichment of CD4+ and CD8+ we reached 68.3-fold and 71.4-fold T cell expansion rates, respectively, in two independent runs. Transduction efficiencies of 77.7% and 55.1% was obtained, and yields of 4.5 x 109 and 3.6 x 109 engineered T cells from the two donors, respectively, within 12 days. Preclinical characterization demonstrated antigen-specific GD2-CAR mediated activation after co-cultivation with GD2-expressing target cells. The functional capacities of the clinical-scale manufactured TRUCKs were similar to TRUCKs generated in laboratory-scale and were not impeded by cryopreservation. IL-18 TRUCKs were activated in an antigen-specific manner by co-cultivation with GD2-expressing target cells indicated by an increased expression of activation markers (e.g. CD25, CD69) on both CD4+ and CD8+ T cells and an enhanced release of pro-inflammatory cytokines and cytolytic mediators (e.g. IL-2, granzyme B, IFN-γ, perforin, TNF-α). Manufactured TRUCKs showed a specific cytotoxicity towards GD2-expressing target cells indicated by lactate dehydrogenase (LDH) release, a decrease of target cell numbers, microscopic detection of cytotoxic clusters and detachment of target cells in real-time impedance measurements (xCELLigence). Following antigen-specific CAR activation of TRUCKs, CAR-triggered release IL-18 was induced, and the cytokine was biologically active, as demonstrated in migration assays revealing specific attraction of monocytes and NK cells by supernatants of TRUCKs co-cultured with GD2-expressing target cells. In conclusion, GMP-compliant manufacturing of TRUCKs is feasible and delivers high quality T cell products

Molecular Ultrasound Imaging of Early Vascular Response in Prostate Tumors Irradiated with Carbon Ions

Individualized treatments with combination of radiotherapy and targeted drugs require knowledge about the behavior of molecular targets after irradiation. Angiogenic marker expression has been studied after conventional radiotherapy, but little is known about marker response to charged particles. For the very first time, we used molecular ultrasound imaging to intraindividually track changes in angiogenic marker expression after carbon ion irradiation in experimental tumors. Expression of intercellular adhesion molecule-1 (ICAM-1) and of αvβ3-integrin in subcutaneous AT-1 prostate cancers in rats treated with carbon ions (16 Gy) was studied using molecular ultrasound and immunohistochemistry. For this purpose, cyanoacrylate microbubbles were synthesized and linked to specific ligands. The accumulation of targeted microbubbles in tumors was quantified before and 36 hours after irradiation. In addition, tumor vascularization was analyzed using volumetric Doppler ultrasound. In tumors, the accumulation of targeted microbubbles was significantly higher than in nonspecific ones and could be inhibited competitively. Before irradiation, no difference in binding of αvβ3-integrin-specific or ICAM-1-specific microbubbles was observed in treated and untreated animals. After irradiation, however, treated animals showed a significantly higher binding of αvβ3-integrin-specific microbubbles and an enhanced binding of ICAM-1-specific microbubbles than untreated controls. In both groups, a decrease in vascularization occurred during tumor growth, but no significant difference was observed between irradiated and nonirradiated tumors. In conclusion, carbon ion irradiation upregulates ICAM-1 and αvβ3-integrin expression in tumor neovasculature. Molecular ultrasound can indicate the regulation of these markers and thus may help to identify the optimal drugs and time points in individualized therapy regimens

Mutational dynamics between primary and relapse neuroblastomas

Neuroblastoma is a malignancy of the developing sympathetic nervous system that is often lethal when relapse occurs. We here used whole-exome sequencing, mRNA expression profiling, array CGH and DNA methylation analysis to characterize 16 paired samples at diagnosis and relapse from individuals with neuroblastoma. The mutational burden significantly increased in relapsing tumors, accompanied by altered mutational signatures and reduced subclonal heterogeneity. Global allele frequencies at relapse indicated clonal mutation selection during disease progression. Promoter methylation patterns were consistent over disease course and were patient specific. Recurrent alterations at relapse included mutations in the putative CHD5 neuroblastoma tumor suppressor, chromosome 9p losses, DOCK8 mutations, inactivating mutations in PTPN14 and a relapse-specific activity pattern for the PTPN14 target YAP. Recurrent new mutations in HRAS, KRAS and genes mediating cell-cell interaction in 13 of 16 relapse tumors indicate disturbances in signaling pathways mediating mesenchymal transition. Our data shed light on genetic alteration frequency, identity and evolution in neuroblastoma