Single-cell atlases often include samples that span locations, laboratories and conditions, leading to complex, nested batch effects in data. Thus, joint analysis of atlas datasets requires reliable data integration. To guide integration method choice, we benchmarked 68 method and preprocessing combinations on 85 batches of gene expression, chromatin accessibility and simulation data from 23 publications, altogether representing >1.2 million cells distributed in 13 atlas-level integration tasks. We evaluated methods according to scalability, usability and their ability to remove batch effects while retaining biological variation using 14 evaluation metrics. We show that highly variable gene selection improves the performance of data integration methods, whereas scaling pushes methods to prioritize batch removal over conservation of biological variation. Overall, scANVI, Scanorama, scVI and scGen perform well, particularly on complex integration tasks, while single-cell ATAC-sequencing integration performance is strongly affected by choice of feature space. Our freely available Python module and benchmarking pipeline can identify optimal data integration methods for new data, benchmark new methods and improve method development.

Cell atlases often include samples that span locations, labs, and conditions, leading to complex, nested batch effects in data. Thus, joint analysis of atlas datasets requires reliable data integration .Choosing a data integration method is a challenge due to the difficulty of defining integration success. Here, we benchmark 38 method and preprocessing combinations on 77 batches of gene expression, chromatin accessibility, and simulation data from 23 publications, altogether representing >1.2 million cells distributed in nine atlas-level integration tasks. Our integration tasks span several common sources of variation such as individuals, species, and experimental labs. We evaluate methods according to scalability, usability, and their ability to remove batch effects while retaining biological variation.Using 14 evaluation metrics, we find that highly variable gene selection improves the performance of data integration methods, whereas scaling pushes methods to prioritize batch removal over conservation of biological variation. Overall, BBKNN, Scanorama, and scVI perform well, particularly on complex integration tasks; Seurat v3 performs well on simpler tasks with distinct biological signals; and methods that prioritize batch removal perform best for ATAC-seq data integration. Our freely available reproducible python module can be used to identify optimal data integration methods for new data, benchmark new methods, and improve method development.2

Computational vision-based flame detection has drawn significant attention in the past decade with camera surveillance systems becoming ubiquitous. Whereas many discriminating features, such as color, shape, texture, etc., have been employed in the literature, this paper proposes a set of motion features based on motion estimators. The key idea consists of exploiting the difference between the turbulent, fast, fire motion, and the structured, rigid motion of other objects. Since classical optical flow methods do not model the characteristics of fire motion (e.g., non-smoothness of motion, non-constancy of intensity), two optical flow methods are specifically designed for the fire detection task: optimal mass transport models fire with dynamic texture, while a data-driven optical flow scheme models saturated flames. Then, characteristic features related to the flow magnitudes and directions are computed from the flow fields to discriminate between fire and non-fire motion. The proposed features are tested on a large video database to demonstrate their practical usefulness. Moreover, a novel evaluation method is proposed by fire simulations that allow for a controlled environment to analyze parameter influences, such as flame saturation, spatial resolution, frame rate, and random noise.

Gastric acid secretion is not only stimulated via the classical known neuronal and hormonal pathways but also by the Ca²⁺-Sensing Receptor (CaSR) located at the basolateral membrane of the acid-secretory gastric parietal cell. Stimulation of CaSR with divalent cations or the potent agonist Gd³⁺ leads to activation of the H⁺/K⁺-ATPase and subsequently to gastric acid secretion. Here we investigated the intracellular mechanism(s) mediating the effects of the CaSR on H⁺/K⁺-ATPase activity in freshly isolated human gastric glands. Inhibition of heterotrimeric G-proteins (G_i and G_o) with pertussis toxin during stimulation of the CaSR with Gd³⁺ only partly reduced the observed stimulatory effect. A similar effect was observed with the PLC inhibitor U73122. The reduction of the H⁺/K⁺-ATPase activity measured after incubation of gastric glands with BAPTA-AM, a chelator of intracellular Ca²⁺, showed that intracellular Ca²⁺ plays an important role in the signalling cascade. TMB-8, a ER Ca²⁺store release inhibitor, prevented the stimulation of H⁺/K⁺-ATPase activity. Also verapamil, an inhibitor of L-type Ca²⁺-channels reduced stimulation suggesting that both the release of intracellular Ca²⁺ from the ER as well as Ca²⁺ influx into the cell are involved in CaSR-mediated H⁺/K⁺-ATPase activation. Chelerythrine, a general inhibitor of protein kinase C, and Gö 6976 which selectively inhibits Ca²⁺-dependent PKC_α and PKC_βI-isozymes completely abolished the stimulatory effect of Gd³⁺. In contrast, Ro 31-8220, a selective inhibitor of the Ca²⁺-independent PKCε and PKC-δ isoforms reduced the stimulatory effect of Gd³⁺ only about 60 %. On the other hand, activation of PKC with DOG led to an activation of H⁺/K⁺-ATPase activity which was only about 60 % of the effect observed with Gd³⁺. Incubation of the parietal cells with PD 098059 to inhibit ERK1/2 MAP-kinases showed a significant reduction of the Gd³⁺ effect. Thus, in the human gastric parietal cell the CaSR is coupled to pertussis toxin sensitive heterotrimeric G-Proteins and requires calcium to enhance the activity of the proton-pump. PLC, ERK 1/2 MAP-kinases as well as Ca²⁺ dependent and Ca²⁺-independent PKC isoforms are part of the down-stream signalling cascade.

Animal behavior is remarkably robust despite constant changes in neural activity. Homeostatic plasticity stabilizes central nervous system (CNS) function on time scales of hours to days. If and how CNS function is stabilized on more rapid time 15 scales remains unknown. Here we discovered that mossy fiber synapses in the mouse cerebellum homeostatically control synaptic efficacy within minutes after pharmacological glutamate receptor impairment. This rapid form of homeostatic plasticity is expressed presynaptically. We show that modulations of readilyreleasable vesicle pool size and release probability normalize synaptic strength in a 20 hierarchical fashion upon acute pharmacological and prolonged genetic receptor perturbation. Presynaptic membrane capacitance measurements directly demonstrate regulation of vesicle pool size upon receptor impairment. Moreover, presynaptic voltage-clamp analysis revealed increased calcium-current density under specific experimental conditions. Thus, homeostatic modulation of presynaptic 25 exocytosis through specific mechanisms stabilizes synaptic transmission in a CNS circuit on time scales ranging from minutes to months. Rapid presynaptic homeostatic plasticity may ensure stable neural circuit function in light of rapid activity-dependent plasticity.30

Sound localization with hearing aids has traditionally been investigated in artificial laboratory settings. These settings are not representative of environments in which hearing aids are used. With individual Head-Related Transfer Functions (HRTFs) and room simulations, realistic environments can be reproduced and the performance of hearing aid algorithms can be evaluated. In this study, four different environments with background noise have been implemented in which listeners had to localize different sound sources. The HRTFs were measured inside the ear canals of the test subjects and by the microphones of Behind-The-Ear (BTEs) hearing aids. In the first experiment the system for virtual acoustics was evaluated by comparing perceptual sound localization results for the four scenes in a real room with a simulated one. In the second experiment, sound localization with three BTE algorithms, an omnidirectional microphone, a monaural cardioid-shaped beamformer and a monaural noise canceler, was examined. The results showed that the system for generating virtual environments is a reliable tool to evaluate sound localization with hearing aids. With BTE hearing aids localization performance decreased and the number of front-back confusions was at chance level. The beamformer, due to its directivity characteristics, allowed the listener to resolve the front-back ambiguity.

Bilateral cochlear implant (CI) users encounter difficulties in localizing sound sources in everyday environments, especially in the presence of background noise and reverberation. They tend to show large directional errors and front-back confusions compared to normal hearing (NH) subjects in the same conditions. In this study, the ability of bilateral CI users to use head movements to improve sound source localization was evaluated. Speech sentences of 0.5, 2, and 4.5 seconds were presented in noise to the listeners in conditions with and without head movements. The results show that for middle and long signal durations, the CI users could significantly reduce the number of front-back confusions. The angular accuracy, however, did not improve. Analysis of head trajectories showed that the CI users had great difficulties in moving their head towards the position of the source, whereas the NH listeners targeted the source loudspeaker correctly.

Human cellular models of neurodegeneration require reproducibility and longevity, which is necessary for simulating these age-dependent diseases. Such systems are particularly needed for TDP-43 proteinopathies, which involve human-specific mechanisms that cannot be directly studied in animal models. To explore the emergence and consequences of TDP-43 pathologies, we generated iPSC-derived, colony morphology neural stem cells (iCoMoNSCs) via manual selection of neural precursors. Single-cell transcriptomics (scRNA-seq) and comparison to independent NSCs, showed that iCoMoNSCs are uniquely homogenous and self-renewing. Differentiated iCoMoNSCs formed a self-organized multicellular system consisting of synaptically connected and electrophysiologically active neurons, which matured into long-lived functional networks. Neuronal and glial maturation in iCoMoNSC-derived cultures was similar to that of cortical organoids. Overexpression of wild-type TDP-43 in a minority of iCoMoNSC-derived neurons led to progressive fragmentation and aggregation, resulting in loss of function and neurotoxicity. scRNA-seq revealed a novel set of misregulated RNA targets coinciding in both TDP-43 overexpressing neurons and patient brains exhibiting loss of nuclear TDP-43. The strongest misregulated target encoded for the synaptic protein NPTX2, which was consistently misaccumulated in ALS and FTLD patient neurons with TDP-43 pathology. Our work directly links TDP-43 misregulation and NPTX2 accumulation, thereby highlighting a new pathway of neurotoxicity.