Why do Employees Leave Their Jobs for Self-Employment? – The Impact of Entrepreneurial Working Conditions in Small Firms

Based on the finding that entrepreneurs who found new firms tend to work as employees of small rather than large firms prior to start-up, we test how different working conditions, which enhance entrepreneurial learning, affect their decision to become entrepreneurs when moderated by firm size. Based on data of the German Socio-Economic Panel (SOEP), we find a significant relationship between entrepreneurial learning (extracted in an orthogonal factor analysis based on twelve working conditions as proxy for entrepreneurial human capital and work experience) and firm size when predicting the probability of leaving paid employment for self-employment. We think, that this is a special kind of knowledge spillover. We also control for other aspects such as gender, age, wage, etc. – factors that may potentially influence the decision to become self-employed. Thus, our analysis sheds new light onto the black box of SMEs as a hotbed of new start-ups.Entrepreneurship, Occupational Choice, Working Conditions, Human Capital

Why do Employees Leave Their Jobs for Self-Employment? – The Impact of Entrepreneurial Working Conditions in Small Firms

Based on the finding that entrepreneurs who found new firms tend to work as employees of small rather than large firms prior to start-up, we test how different working conditions, which enhance entrepreneurial learning, affect their decision to become entrepreneurs when moderated by firm size. Based on data of the German Socio-Economic Panel (SOEP), we find a significant relationship between entrepreneurial learning (extracted in an orthogonal factor analysis based on twelve working conditions as proxy for entrepreneurial human capital and work experience) and firm size when predicting the probability of leaving paid employment for self-employment. We think, that this is a special kind of knowledge spillover. We also control for other aspects such as gender, age, wage, etc. – factors that may potentially influence the decision to become self-employed. Thus, our analysis sheds new light onto the black box of SMEs as a hotbed of new start-ups

Why do Employees Leave Their Jobs for Self-Employment? – The Impact of Entrepreneurial Working Conditions in Small Firms

Based on the finding that entrepreneurs who found new firms tend to work as employees of small rather than large firms prior to start-up, we test how different working conditions, which enhance entrepreneurial learning, affect their decision to become entrepreneurs when moderated by firm size. Based on data of the German Socio-Economic Panel (SOEP), we find a significant relationship between entrepreneurial learning (extracted in an orthogonal factor analysis based on twelve working conditions as proxy for entrepreneurial human capital and work experience) and firm size when predicting the probability of leaving paid employment for self-employment. We think, that this is a special kind of knowledge spillover. We also control for other aspects such as gender, age, wage, etc. – factors that may potentially influence the decision to become self-employed. Thus, our analysis sheds new light onto the black box of SMEs as a hotbed of new start-ups

Training and Evaluation of Deep Policies using Reinforcement Learning and Generative Models

We present a data-efficient framework for solving sequential decision-making problems which exploits the combination of reinforcement learning (RL) and latent variable generative models. The framework, called GenRL, trains deep policies by introducing an action latent variable such that the feed-forward policy search can be divided into two parts: (i) training a sub-policy that outputs a distribution over the action latent variable given a state of the system, and (ii) unsupervised training of a generative model that outputs a sequence of motor actions conditioned on the latent action variable. GenRL enables safe exploration and alleviates the data-inefficiency problem as it exploits prior knowledge about valid sequences of motor actions. Moreover, we provide a set of measures for evaluation of generative models such that we are able to predict the performance of the RL policy training prior to the actual training on a physical robot. We experimentally determine the characteristics of generative models that have most influence on the performance of the final policy training on two robotics tasks: shooting a hockey puck and throwing a basketball. Furthermore, we empirically demonstrate that GenRL is the only method which can safely and efficiently solve the robotics tasks compared to two state-of-the-art RL methods.Comment: arXiv admin note: substantial text overlap with arXiv:2007.1313

Immunophenotyping and oncogene amplifications in tumors of the papilla of Vater

Carcinomas of the ampulla of Vater are rare and assumed to generally arise from preexisting adenomas (adenoma-carcinoma sequence). Histologically, distinct subtypes can be distinguished that were shown to differ significantly in terms of clinical outcome. Since pathologists usually receive bioptic tissue samples of ampullary tumors obtained during endoscopy, accurate classification of carcinoma subtypes can sometimes be difficult on morphological criteria alone. We therefore performed immunohistochemistry using a panel of established marker proteins (CK7, CK20, p21, p27, ESA, bax, and ephrin-B2) on 175 carcinoma, 111 adenoma, and 152 normal mucosa specimens of the ampulla of Vater and identified distinct immunoprofiles for every carcinoma subtype. Fluorescence in situ hybridization analyses of therapeutic target genes (c-myc, EGFR1, CCND1, HER2) found CCND1 to represent the most frequently amplified gene in our series (7.5%

The Anti-Fibrotic Effect of Cold Atmospheric Plasma on Localized Scleroderma In Vitro and In Vivo

Cold Atmospheric Plasma (CAP) has shown promising results in the treatment of various skin diseases. The therapeutic effect of CAP on localized scleroderma (LS), however, has not yet been evaluated. We investigated the effects of CAP on LS by comparing human normal fibroblasts (hNF), human TGF-β-activated fibroblasts (hAF), and human localized scleroderma-derived fibroblasts (hLSF) after direct CAP treatment, co-cultured with plasma-treated human epidermal keratinocytes (hEK) and with an experimental murine model of scleroderma. In hAF and hLSF, 2 min CAP treatment with the MicroPlaSterβ® plasma torch did not affect pro-fibrotic gene expression of alpha smooth muscle actin, fibroblast activating protein, and collagen type I, however, it promoted re-expression of matrix metalloproteinase 1. Functionally, CAP treatment reduced cell migration and stress fiber formation in hAF and hLSF. The relevance of CAP treatment was confirmed in an in vivo model of bleomycin-induced dermal fibrosis. In this model, CAP-treated mice showed significantly reduced dermal thickness and collagen deposition as well as a decrease in both alpha smooth muscle actin-positive myofibroblasts and CD68-positive macrophages in the affected skin in comparison to untreated fibrotic tissue. In conclusion, this study provides the first evidence for the successful use of CAP for treating LS and may be the basis for clinical trials including patients with LS

Biological effects of a new ultraviolet A1 prototype based on light‐emitting diodes on the treatment of localized scleroderma

Ultraviolet A(1)(UVA(1)) phototherapy (spectral range 340-400 nm) is a well-established treatment option for various skin diseases such as localized scleroderma. Recent improvements of conventional UVA(1)light sources (metal-halide or fluorescent lamps) have brought attention to a new light-emitting diode (LED) technology with remarkable advantages in handling and clinical routine. This study provides a preclinical histological and molecular evaluation of an LED-based UVA(1)prototype with a narrower spectral range (360-400 nm) for treating localized scleroderma. Scleroderma mouse models and fibroblasts in vitro were exposed to LED-based UVA(1)phototherapy or to irradiation with a commercially available metal-halide lamp emitting low-dose (20, 40 J/cm(2)), medium-dose (60 J/cm(2)) and high-dose (80, 100 J/cm(2)) UVA(1)light. Both UVA(1)light sources affected inflammatory genes (IL-1 alpha and IL-6) and growth factors (TGFss-1 and TGFss-2). Increased collagen type 1 was reduced after UVA(1)phototherapy. Matrix metalloproteinase-1 was more enhanced after a medium dose of LED-based UVA(1)phototherapy than after conventional treatment. In vivo, dermal thickness and the amount of collagen were reduced after both treatment methods. Remarkably, myofibroblasts were more effectively reduced by a medium dose of LED-based UVA(1)phototherapy. The study indicates that LED-based UVA(1)phototherapy yields similar or even better results than conventional treatment. In terms of biosafety and patient comfort, LED-based UVA(1)phototherapy offers clear advantages over conventional treatment because of the use of a narrower and less harmful UVA(1)spectrum, less heat generation and shorter treatment times at the same irradiation intensity. Clinical studies are required to confirm these results in patients with localized scleroderma

Cryogel-supported stem cell factory for customized sustained release of bispecific antibodies for cancer immunotherapy

Combining stem cells with biomaterial scaffolds provides a promising strategy for the development of drug delivery systems. Here we propose an innovative immunotherapeutic organoid by housing human mesenchymal stromal cells (MSCs), gene-modified for the secretion of an anti-CD33-anti-CD3 bispecific antibody (bsAb), in a small biocompatible star-shaped poly(ethylene glycol)-heparin cryogel scaffold as a transplantable and low invasive therapeutic machinery for the treatment of acute myeloid leukemia (AML). The macroporous biohybrid cryogel platform displays effectiveness in supporting proliferation and survival of bsAb-releasing-MSCs overtime in vitro and in vivo, avoiding cell loss and ensuring a constant release of sustained and detectable levels of bsAb capable of triggering T-cell-mediated anti-tumor responses and a rapid regression of CD33 + AML blasts. This therapeutic device results as a promising and safe alternative to the continuous administration of short-lived immunoagents and paves the way for effective bsAb-based therapeutic strategies for future tumor treatments

Retargeting of UniCAR T cells with an in vivo synthesized target module directed against CD19 positive tumor cells

Recent treatments of leukemias with T cells expressing chimeric antigen receptors (CARs) underline their impressive therapeutic potential but also their risk of severe side effects including cytokine release storms and tumor lysis syndrome. In case of cross-reactivities, CAR T cells may also attack healthy tissues. To overcome these limitations, we previously established a switchable CAR platform technology termed UniCAR. UniCARs are not directed against typical tumor-associated antigens (TAAs) but instead against a unique peptide epitope: Fusion of this peptide epitope to a recombinant antibody domain results in a target module (TM). TMs can cross-link UniCAR T cells with tumor cells and thereby lead to their destruction. So far, we constructed TMs with a short half-life. The fast turnover of such a TM allows to rapidly interrupt the treatment in case severe side effects occur. After elimination of most of the tumor cells, however, longer lasting TMs which have not to be applied via continous infusion would be more convenient for the patient. Here we describe and characterize a TM for retargeting UniCAR T cells to CD19 positive tumor cells. Moreover, we show that the TM can efficiently be produced in vivo from producer cells housed in a sponge-like biomimetic cryogel and, thereby, serving as an in vivo TM factory for an extended retargeting of UniCAR T cells to CD19 positive leukemic cells