
埃尔朗根-纽伦堡大学(全名弗里德里希-亚历山大 埃尔朗根-纽伦堡大学,德文:Friedrich-Alexander-Universität Erlangen-Nürnberg,缩写:FAU)是德国一座历史悠久的大学,位于埃尔朗根和纽伦堡。 埃尔朗根-纽伦堡大学于1743年始建于拜罗伊特,后迁至埃尔朗根。1972年位于纽伦堡的经济及教育学院并入大学。成为了巴伐利亚州第二大国立综合性大学。埃尔朗根-纽伦堡大学的名字来源于大学的创始人勃兰登堡-拜罗伊特侯爵弗里德里希以及它的资助人勃兰登堡-安斯巴赫侯爵克里斯蒂安·弗雷德里克·查尔斯·亚历山大。 埃朗根-纽伦堡大学与亚琛工业大学,慕尼黑工业大学,达姆施塔特工业大学,德累斯顿工业大学等同为欧洲顶尖工业管理者高校联盟成员,并且拥有出色的医学院和技术学院。其中材料科学,能源工程,通信系统,电气工程,医学等专业在QS世界大学排名,上海交大世界大学学术排名(ARWU)中常年位居德国前10。 学校建校以来产生过4位诺贝尔奖得主,并且培养了众多优秀的科学家,工程师,哲学家和医学家等。
The present guideline summarizes all aspects of patch testing for the diagnosis of contact allergy in patients suspected of suffering, or having been suffering, from allergic contact dermatitis or other delayed-type hypersensitivity skin and mucosal conditions. Sections with brief descriptions and discussions of different pertinent topics are followed by a highlighted short practical recommendation. Topics comprise, after an introduction with important definitions, materials, technique, modifications of epicutaneous testing, individual factors influencing the patch test outcome or necessitating special considerations, children, patients with occupational contact dermatitis and drug eruptions as special groups, patch testing of materials brought in by the patient, adverse effects of patch testing, and the final evaluation and patient counselling based on this judgement. Finally, short reference is made to aspects of (continuing) medical education and to electronic collection of data for epidemiological surveillance.
The digital transformation of healthcare is rapidly reshaping neurology, particularly in the field of movement disorders, where continuous monitoring, long disease trajectories, and complex multimodal care create a high demand for innovative solutions. Wearable sensors, digital diagnostics, app-based therapeutics, and integrated hybrid care networks and digital supported care pathways promise earlier diagnosis, personalized treatment and care management, and improved long-term outcomes. However, real-world implementation in managed outpatient care remains fragmented and faces major barriers beyond pure technological feasibility. This position paper critically reviews the current state of digital technologies in movement disorder care, identifies key systemic, ethical, and economic roadblocks, and proposes a pragmatic roadmap toward a realistic and ethically sound digital outpatient clinic. We argue that the future digital clinic will not be defined solely by technical progress, but by how consciously healthcare systems integrate digital tools to hybrid care solutions while preserving human-centered, equitable, and evidence-based care.
Bioreactors in biofabrication and tissue engineering enable dynamic cell and tissue culture under controlled conditions while applying external stimuli such as mechanical or electrical signals. Together, these features mimic the in vivo environment and support functional tissue formation for implantation or model systems. Most current bioreactors focus on medium perfusion and mechanical or electrical stimulation, but often lack real-time monitoring, which is essential for quality control. To address this gap, this work presents an additively manufactured bioreactor that integrates dynamic perfusion, electrical stimulation, and in-line microscopy and sensor monitoring for culturing 3D-bioprinted constructs. Three bioinks containing C2C12 myoblasts were 3D-printed and cultured in the system, with continuous tracking of pH and temperature and comparison to static controls. Laminar perfusion improved cell viability and spreading in GelMA and ADA-GEL bioinks, with faster myoblast alignment observed in ADA-GEL after 3 days. Platinum-coated copper electrodes embedded in the design produced electric fields of at least 10 V & centerdot;cm- 1. As a proof of principle, isolated murine interossei plantares myofibers were placed in the chamber and electrically stimulated to induce twitching. Overall, this bioreactor demonstrates strong potential as a platform for real-time tissue monitoring and studying customized stimuli during tissue development.
Inflammatory bowel diseases present with elevated levels of intestinal epithelial cell (IEC) death, which compromises the gut barrier, activating immune cells and triggering more IEC death. The endogenous signals that prevent IEC death and break this vicious cycle, allowing resolution of intestinal inflammation, remain largely unknown. Here we show that prostaglandin E2 signalling via the E-type prostanoid receptor 4 (EP4) on IECs represses epithelial necroptosis and induces resolution of colitis. We found that EP4 expression correlates with an improved IBD outcome and that EP4 activation induces a transcriptional signature consistent with resolution of intestinal inflammation. We further show that dysregulated necroptosis prevents resolution, and EP4 agonism suppresses necroptosis in human and mouse IECs. Mechanistically, EP4 signalling on IECs converges on receptor-interacting protein kinase 1 to suppress tumour necrosis factor-induced activation and membrane translocation of the necroptosis effector mixed-lineage kinase domain-like pseudokinase. In summary, our study indicates that EP4 promotes the resolution of colitis by suppressing IEC necroptosis.
Moderators are intended to clarify when, where, and for whom interventions work, yet null moderator results are often omitted from the published record. We term this practice “reporting after moderators are significant” (RAMSing) and examine its scope and consequences in STEM education meta-research. Drawing on an umbrella review of 89 meta-analyses comprising 1,786 moderator effect sizes, we found a substantial visibility gap: non-significant moderator effect sizes showed markedly lower relative visibility than the most strongly selected results ( ≈ 0.40). To address this bias, we combined structural mapping with two bias-robust Bayesian frameworks, RoBMA-PSMA and RoBMA-Regression, to estimate bias-adjusted moderator effects, derive field-specific benchmarks, and estimate realistic evidential requirements for moderator testing. The overall bias-adjusted mean moderator effect was g = 0.27 (95 = 0.48). Modeling a five-level moderator-theme classification substantially improved fit (BFInc = 350) and slightly reduced residual heterogeneity ( = 0.44). RAMSing-adjusted benchmarks placed the 25th, 50th, and 75th percentiles of |g| at 0.18, 0.38, and 0.64, respectively, all below both Cohen’s conventional heuristics and the raw empirical quartiles. Prospective power analyses further indicated that, under the assumptions examined here (g = 0.38, ^2 = 0.24, = 0.05), approximately 14 independent effect sizes per moderator level are needed to detect a typical moderator effect. These findings indicate that RAMSing is likely an important source of distortion in moderator-based inference within this corpus. The workflow and openly available toolkit introduced here provide a practical framework for detecting and bias-adjusting RAMSing, and for supporting practices designed to reduce it in STEM education and other fields that rely on meta-analytic moderator evidence.