MIA is an open-source standalone deep learning application for microscopic image analysis.

In recent years, the amount of data generated by imaging techniques has grown rapidly, along with increasing computational power and the development of deep learning algorithms. To address the need for powerful automated image analysis tools for a broad range of applications in the biomedical sciences, the Microscopic Image Analyzer (MIA) was developed. MIA combines a graphical user interface that obviates the need for programming skills with state-of-the-art deep-learning algorithms for segmentation, object detection, and classification. It runs as a standalone, platform-independent application and uses open data formats, which are compatible with commonly used open-source software packages. The software provides a unified interface for easy image labeling, model training, and inference. Furthermore, the software was evaluated in a public competition and performed among the top three for all tested datasets.

[Application areas of artificial intelligence in the context of One Health with a focus on antimicrobial resistance]. / Anwendungsbereiche von künstlicher Intelligenz im Kontext von One Health mit Fokus auf antimikrobielle Resistenzen.

Societal health is facing a number of new challenges, largely driven by ongoing climate change, demographic ageing, and globalization. The One Health approach links human, animal, and environmental sectors with the goal of achieving a holistic understanding of health in general. To implement this approach, diverse and heterogeneous data streams and types must be combined and analyzed. To this end, artificial intelligence (AI) techniques offer new opportunities for cross-sectoral assessment of current and future health threats. Using the example of antimicrobial resistance as a global threat in the One Health context, we demonstrate potential applications and challenges of AI techniques.This article provides an overview of different applications of AI techniques in the context of One Health and highlights their challenges. Using the spread of antimicrobial resistance (AMR), an increasing global threat, as an example, existing and future AI-based approaches to AMR containment and prevention are described. These range from novel drug development and personalized therapy, to targeted monitoring of antibiotic use in livestock and agriculture, to comprehensive environmental surveillance.

Neddylation regulates excitatory synaptic transmission and plasticity.

Post-translational modifications, like phosphorylation, ubiquitylation, and sumoylation, have been shown to impact on synaptic neurotransmission by modifying pre- and postsynaptic proteins and therefore alter protein stability, localization, or protein-protein interactions. Previous studies showed that post-translational modifications are essential during the induction of synaptic plasticity, defined by a major reorganization of synaptic proteins. We demonstrated before that neddylation, a post-translational modification that covalently binds Nedd8 to lysine-residues, strongly affects neuronal maturation and spine stability. We now analysed the consequences of inhibiting neddylation on excitatory synaptic transmission and plasticity, which will help to narrow down possible targets, to make educated guesses, and test specific candidates. Here, we show that acute inhibition of neddylation impacts on synaptic neurotransmission before morphological changes occur. Our data indicate that pre- and postsynaptic proteins are neddylated since the inhibition of neddylation impacts on presynaptic release probability and postsynaptic receptor stabilization. In addition, blocking neddylation during the induction of long-term potentiation and long-term inhibition abolished both forms of synaptic plasticity. Therefore, this study shows the importance of identifying synaptic targets of the neddylation pathway to understand the regulation of synaptic transmission and plasticity.

In vivo imaging demonstrates dendritic spine stabilization by SynCAM 1.

Formation and stability of synapses are required for proper brain function. While it is well established that synaptic adhesion molecules are important regulators of synapse formation, their specific role during different phases of synapse development remains unclear. To investigate the function of the synaptic cell adhesion molecule SynCAM 1 in the formation, stability, and maintenance of spines we used 2-photon in vivo imaging to follow individual spines over a long period of time. In SynCAM 1 knockout mice the survival rate of existing spines was reduced and fewer filopodia-like structures were converted into stable spines. SynCAM 1(flag) overexpression resulted in more stable spines and fewer filopodia-like structures. When SynCAM 1(flag) overexpression is turned on the spine density rapidly increases within a few days. Interestingly, the spine density stayed at an elevated level when SynCAM 1(flag) overexpression was turned off. Our data indicate that the SynCAM 1 induced altered spine density is not caused by the formation of newly emerging protrusions, instead SynCAM 1 stabilizes nascent synaptic contacts which promotes their maturation. Concomitant with the synaptic stabilization, SynCAM 1 generally prolongs the lifetime of spines. In summary, we demonstrate that SynCAM 1 is a key regulator of spine stability.

SynCAM 1 improves survival of adult-born neurons by accelerating synapse maturation.

The survival of adult-born dentate gyrus granule cells critically depends on their synaptic integration into the existing neuronal network. Excitatory inputs are thought to increase the survival rate of adult born neurons. Therefore, whether enhancing the stability of newly formed excitatory synapses by overexpressing the synaptic cell adhesion molecule SynCAM 1 improves the survival of adult-born neurons was tested. Here it is shown that overexpression of SynCAM 1 improves survival of adult-born neurons, but has no effect on the proliferation rate of precursor cells. As expected, overexpression of SynCAM 1 increased the synapse density in adult-born granule neurons. While adult-born granule neurons have very few functional synapses 15 days after birth, it was found that at this age adult-born neurons in SynCAM 1 overexpressing mice exhibited around three times more excitatory synapses, which were stronger than synapses of adult-born neurons of control littermates. In summary, the data indicated that additional SynCAM 1 accelerated synapse maturation, which improved the stability of newly formed synapses and in turn increased the likelihood of survival of adult-born neurons.