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Drawing on signaling theory, this study provides preliminary evidence that prior financing certifies firm quality to investors and reduces information asymmetries in equity crowdfunding. We examine 221 business plans and project descriptions of start-ups that ran equity crowdfunding campaigns on Crowdcube in 2017 and 2018. Almost half of the start-ups had previously raised funds through business angels, venture capitalists, crowdfunding, or grants. Prior financing positively affects campaign success. Overall, the effect is larger for firms backed by multiple investor types and for firms that have run successful crowdfunding before. To isolate the quality signal from the additional benefits related to an affiliation with other investors, we analyze whether the effect of prior financing is moderated by the uncertainty around a project. In support of a signaling effect, preliminary evidence suggests that prior financing is most relevant for firms in the uncertain seed stage. Among the different investor types, we find that, in particular, an affiliation with venture capitalists signals quality. Such an affiliation is more important for firms with low levels of human and social capital. Our study adds to the understanding of how equity crowdfunding interacts with traditional forms of entrepreneurial finance.

Equity crowdfunding has the potential to democratize entrepreneurial finance and provide female entrepreneurs with new and equal access to early-stage financing. In this paper, we present first empirical evidence on gender stereotypes in the context of technology ventures in equity crowdfunding. Drawing on signaling and gender role congruity theory, we hypothesize that quality signals have different effects depending on whether they are sent by male or female entrepreneurs. Results taken from a sample of 263 equity crowdfunding campaigns run by technology ventures confirm our hypotheses. In line with gender stereotypes, management experience is beneficial for male entrepreneurs but detrimental for female entrepreneurs. Interestingly, media coverage as a third-party signal has the oppositive effect, being more effective for female entrepreneurs.

Drawing on self-determination theory (SDT), this study examines differences in the motivation of backers to support cultural and commercial entrepreneurs through reward crowdfunding. We propose that backers of commercial campaigns are a community of early-customers motivated by the prospects of attractive product offerings, while backers of cultural projects constitute a distinct community motivated to support capital-constrained cultural entrepreneurs and connect with like-minded individuals. We use data from the largest German crowdfunding platform, Startnext, and analyze 2334 rewards from 225 cultural and commercial projects. Our results provide support for our hypotheses: Rewards involving price discounts matter particularly for backers of commercial projects and rewards that engage backers with their community matter more for cultural backers. Surprisingly, however, backers of cultural projects are not altruistic; they are no more likely than commercial backers to support campaigns selflessly in response to symbolic rewards.

Unfortunately, the original version of this article was published online with error. The data in Tables 1, 3, 4, 5 and 6 were incorrectly displayed and aligned by the Springer proofreaders/or in the proofread stage of Springer. The corrected Tables 1, 3, 4, 5 and 6 are shown in the next page.

Background Timely diagnosis and treatment are essential in the effective management of inflammatory rheumatic diseases (IRDs). Symptom checkers (SCs) promise to accelerate diagnosis, reduce misdiagnoses, and guide patients more effectively through the health care system. Although SCs are increasingly used, there exists little supporting evidence. Objective To assess the diagnostic accuracy, patient-perceived usability, and acceptance of two SCs: (1) Ada and (2) Rheport. Methods Patients newly presenting to a German secondary rheumatology outpatient clinic were randomly assigned in a 1:1 ratio to complete Ada or Rheport and consecutively the respective other SCs in a prospective non-blinded controlled randomized crossover trial. The primary outcome was the accuracy of the SCs regarding the diagnosis of an IRD compared to the physicians’ diagnosis as the gold standard. The secondary outcomes were patient-perceived usability, acceptance, and time to complete the SC. Results In this interim analysis, the first 164 patients who completed the study were analyzed. 32.9% (54/164) of the study subjects were diagnosed with an IRD. Rheport showed a sensitivity of 53.7% and a specificity of 51.8% for IRDs. Ada’s top 1 (D1) and top 5 disease suggestions (D5) showed a sensitivity of 42.6% and 53.7% and a specificity of 63.6% and 54.5% concerning IRDs, respectively. The correct diagnosis of the IRD patients was within the Ada D1 and D5 suggestions in 16.7% (9/54) and 25.9% (14/54), respectively. The median System Usability Scale (SUS) score of Ada and Rheport was 75.0/100 and 77.5/100, respectively. The median completion time for both Ada and Rheport was 7.0 and 8.5 min, respectively. Sixty-four percent and 67.1% would recommend using Ada and Rheport to friends and other patients, respectively. Conclusions While SCs are well accepted among patients, their diagnostic accuracy is limited to date. Trial registration DRKS.de, DRKS00017642 . Registered on 23 July 2019

ObjectivesTo better understand the factors that influence the humoral immune response to vaccination against SARS-CoV-2 in patients with immune-mediated inflammatory diseases (IMIDs).MethodsPatients and controls from a large COVID-19 study, with (1) no previous history of COVID-19, (2) negative baseline anti-SARS-CoV-2 IgG test and (3) SARS-CoV-2 vaccination at least 10 days before serum collection were measured for anti-SARS-CoV-2 IgG. Demographic, disease-specific and vaccination-specific data were recorded.ResultsVaccination responses from 84 patients with IMID and 182 controls were analysed. While all controls developed anti-SARS-CoV-2 IgG, five patients with IMID failed to develop a response (p=0.003). Moreover, 99.5% of controls but only 90.5% of patients with IMID developed neutralising antibody activity (p=0.0008). Overall responses were delayed and reduced in patients (mean (SD): 6.47 (3.14)) compared with controls (9.36 (1.85); p<0.001). Estimated marginal means (95% CI) adjusted for age, sex and time from first vaccination to sampling were 8.48 (8.12–8.85) for controls and 6.90 (6.45–7.35) for IMIDs. Significantly reduced vaccination responses pertained to untreated, conventionally and anticytokine treated patients with IMID.ConclusionsImmune responses against the SARS-CoV-2 are delayed and reduced in patients with IMID. This effect is based on the disease itself rather than concomitant treatment.

Immune-mediated inflammatory diseases (IMIDs) of the joints, gut and skin are treated with inhibitors of inflammatory cytokines. These cytokines are involved in the pathogenesis of coronavirus disease 2019 (COVID-19). Investigating anti-SARS-CoV-2 antibody responses in IMIDs we observe a reduced incidence of SARS-CoV-2 seroconversion in IMID patients treated with cytokine inhibitors compared to patients receiving no such inhibitors and two healthy control populations, despite similar social exposure. Hence, cytokine inhibitors seem to at least partially protect from SARS-CoV-2 infection. Cytokine storm seems to be a common feature of severe COVID-19 pathology. Here, the authors show a reduced rate of SARS-CoV2 positivity in a large population of patients with immune-mediated inflammatory diseases if they are already being treated with cytokine or JAK inhibitors, indicating these treatments are safe to continue and are possibly protective against COVID19.

Recent advancements in hybrid photonic integrated circuits (PICs) for wireless communications are reviewed, with a focus on innovations developed at Fraunhofer HHI. This work leverages hybrid integration technology, which combines indium phosphide (InP) active elements, silicon nitride (Si3N4) low-loss waveguides, and high-efficient thermal-optical tunable polymers with micro-optical functions to achieve fully integrated wireless transceivers. Key contributions include (1) On-chip optical injection locking for generating phase-locked optical beat notes at 45 GHz, enabled by cascaded InP phase modulators and hybrid InP/polymer tunable lasers with a 3.8 GHz locking range. (2) Waveguide-integrated THz emitters and receivers, featuring photoconductive antennas (PCAs) with a 22× improved photoresponse compared to top-illuminated designs, alongside scalable 1 × 4 PIN-PD and PCA arrays for enhanced power and directivity. (3) Beam steering at 300 GHz using a polymer-based optical phased array (OPA) integrated with an InP antenna array, achieving continuous steering across 20° and a 10.6 dB increase in output power. (4) Demonstration of fully integrated hybrid wireless transceiver PICs combining InP, Si3N4, and polymer material platforms, validated through key component characterization, on-chip optical frequency comb generation, and coherent beat note generation at 45 GHz. These advancements result in compact form factors, reduced power consumption, and enhanced scalability, positioning PICs as an enabling technology for future high-speed wireless networks.

BackgroundInflammatory rheumatic diseases (IRD) are often diagnosed too late due to non-specific symptoms and the lack of specialists in rheumatology. Digital diagnostic decision support systems (DDSS) promise to accelerate diagnosis and decrease the overall healthcare burden.ObjectivesTo assess the ability of an artificial intelligence (AI)-based symptom checker (Ada) and an online self-referral tool (Rheport) to diagnose inflammatory rheumatic diseases (IRD).MethodsIn a prospective, multicenter open-label controlled randomized crossover trial patients newly presenting to a rheumatology center were randomly assigned in a 1:1 ratio to complete a symptom assessment with Ada or Rheport followed by a crossover to the other respective diagnostic decision support system (DDSS). The primary outcome was correct identification of a patient with IRD by the DDSS, defined as the presence of any IRD in the list of suggested diagnoses with Ada or a pre-specified threshold score with Rheport. Physicians’ diagnosis was the gold standard.ResultsIn total, 600 patients were included and 214 (36%) patients were eventually diagnosed with an IRD by a physician. Rheport showed a sensitivity of 62% and specificity of 47% for IRDs. Ada’s top 1 (D1) and top 5 disease suggestions (D5) showed a sensitivity of 52% and 66% and a specificity of 68% and 54% concerning IRDs, respectively. Ada, in comparison to Rheport, was more likely to correctly identify patients with an IRD when used as the first DDSS (OR: 1.09, 95% CI: 1.01 to 1.18) however this finding was not consistent after cross-over (OR: 0.97, 95% CI: 0.90 to 1.05).ConclusionThe diagnostic capability of both DDSS for IRDs was not promising in this high-prevalence patient population referred for subspecialty evaluation. Although the overall numbers suggest that AI-based Ada demonstrated a slightly higher specificity and sensitivity compared to the questionnaire-based Rheport, Ada was not consistently better than Rheport in correctly identifying patients with an IRD when the use sequence of the apps was taken into account. Our results indicate that, strict regulation and drastic improvement is necessary to ensure safety and effectiveness of DDSS.AcknowledgementsThis study was partially funded by Novartis Pharma GmbH.Disclosure of InterestsJohannes Knitza Speakers bureau: Abbvie, Novartis, Lilly, Medac, BMS, Sanofi, Amgen, Gilead, UCB, ABATON, GSK, Werfen, Vila Health, Böhringer Ingelheim, Janssen, Galapagos, Chugai, Celltrion, Grant/research support from: This study has been partially supported by Novartis Pharma GmbH. Others: Abbvie, Novartis, Thermo Fisher, UCB, ABATON, Sanofi, DFG, EIT Health, Koray Tascilar: None declared, Franziska Fuchs: None declared, Jacob Mohn: None declared, David Simon: None declared, Arnd Kleyer: None declared, Christina Bergmann: None declared, Hannah Labinsky: None declared, Harriet Morf: None declared, Elizabeth Araujo: None declared, Daniela Bohr: None declared, Felix Muehlensiepen: None declared, Matthias Englbrecht: None declared, Wolfgang Vorbrüggen: None declared, Cay-Benedict von der Decken: None declared, Stefan Kleinert: None declared, Andreas Ramming: None declared, Joerg Distler: None declared, Peter Bartz-Bazzanella: None declared, Nicolas Vuillerme: None declared, Georg Schett: None declared, Martin Welcker Grant/research support from: Novartis Pharma GmbH, Axel Hueber Grant/research support from: Novartis Pharma GmbH.

Symptom checkers are increasingly used to assess new symptoms and navigate the health care system. The aim of this study was to compare the accuracy of an artificial intelligence (AI)-based symptom checker (Ada) and physicians regarding the presence/absence of an inflammatory rheumatic disease (IRD). In this survey study, German-speaking physicians with prior rheumatology working experience were asked to determine IRD presence/absence and suggest diagnoses for 20 different real-world patient vignettes, which included only basic health and symptom-related medical history. IRD detection rate and suggested diagnoses of participants and Ada were compared to the gold standard, the final rheumatologists’ diagnosis, reported on the discharge summary report. A total of 132 vignettes were completed by 33 physicians (mean rheumatology working experience 8.8 (SD 7.1) years). Ada’s diagnostic accuracy (IRD) was significantly higher compared to physicians (70 vs 54%, p = 0.002) according to top diagnosis. Ada listed the correct diagnosis more often compared to physicians (54 vs 32%, p < 0.001) as top diagnosis as well as among the top 3 diagnoses (59 vs 42%, p < 0.001). Work experience was not related to suggesting the correct diagnosis or IRD status. Confined to basic health and symptom-related medical history, the diagnostic accuracy of physicians was lower compared to an AI-based symptom checker. These results highlight the potential of using symptom checkers early during the patient journey and importance of access to complete and sufficient patient information to establish a correct diagnosis.