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Spermatogenesis, the complex process of male germ cell proliferation, differentiation, and maturation, is the basis of male fertility. In the seminiferous tubules of the testes, spermatozoa are constantly generated from spermatogonial stem cells through a stereotyped sequence of mitotic and meiotic divisions. The basic physiological principles, however, that control both maturation and luminal transport of the still immotile spermatozoa within the seminiferous tubules remain poorly, if at all, defined. Here, we show that coordinated contractions of smooth muscle-like testicular peritubular cells provide the propulsive force for luminal sperm transport toward the rete testis. Using a mouse model for in vivo imaging, we describe and quantify spontaneous tubular contractions and show a causal relationship between peritubular Ca 2+ waves and peristaltic transport. Moreover, we identify P2 receptor-dependent purinergic signaling pathways as physiological triggers of tubular contractions both in vitro and in vivo. When challenged with extracellular ATP, transport of luminal content inside the seminiferous tubules displays stage-dependent directionality. We thus suggest that paracrine purinergic signaling coordinates peristaltic recurrent contractions of the mouse seminiferous tubules to propel immotile spermatozoa to the rete testis. As sperm develop in the testis, the immature cells must make their way through a maze of small tubes known as seminiferous tubules. However, at this stage, the cells do not yet move the long tails that normally allow them to ‘swim’; it is therefore unclear how they are able to move through the tubules. Now, Fleck, Kenzler et al. have showed that, in mice, muscle-like cells within the walls of seminiferous tubules can create waves of contractions that push sperm along. Further experiments were then conducted on cells grown in the laboratory. This revealed that a signaling molecule called ATP orchestrates the moving process by activating a cascade of molecular events that result in contractions. Fleck, Kenzler et al. then harnessed an advanced microscopy technique to demonstrate that this mechanism occurs in living mice. Together, these results provide a better understanding of how sperm mature, which could potentially be relevant for both male infertility and birth control.

The beet cyst nematode Heterodera schachtii is a plant pest responsible for crop loss on a global scale. Here, we introduce a high-throughput system based on computer vision that allows quantifying beet cyst nematode infestation and measuring phenotypic traits of cysts. After recording microscopic images of soil sample extracts in a standardized setting, an instance segmentation algorithm serves to detect nematode cysts in these images. In an evaluation using both ground truth samples with known cyst numbers and manually annotated images, the computer vision approach produced accurate nematode cyst counts, as well as accurate cyst segmentations. Based on such segmentations, cyst features could be computed that served to reveal phenotypical differences between nematode populations in different soils and in populations observed before and after the sugar beet planting period. The computer vision approach enables not only fast and precise cyst counting, but also phenotyping of cyst features under different conditions, providing the basis for high-throughput applications in agriculture and plant breeding research. Source code and annotated image data sets are freely available for scientific use.

Deep learning (DL) holds great promise to improve medical diagnostics, including pathology. Current DL research mainly focuses on performance. DL implementation potentially leads to environmental consequences but approaches for assessment of both performance and carbon footprint are missing. Here, we explored an approach for developing DL for pathology, which considers both diagnostic performance and carbon footprint, calculated as CO 2 or equivalent emissions (CO 2 eq). We evaluated various DL architectures used in computational pathology, including a large foundation model, across two diagnostic tasks of low and high complexity. We proposed a metric termed ‘environmentally sustainable performance’ (ESPer), which quantitatively integrates performance and operational CO 2 eq during training and inference. While some DL models showed comparable diagnostic performance, ESPer enabled prioritizing those with less carbon footprint. We also investigated how data reduction approaches can improve the ESPer of individual models. This study provides an approach facilitating the development of environmentally friendly, sustainable medical AI.

Imaging in three dimensions is necessary for thick tissues and small organisms. This is possible with tomographic optical microscopy techniques such as confocal, multiphoton and light sheet microscopy. All these techniques suffer from anisotropic resolution and limited penetration depth. In the past, Multiview microscopy—imaging the sample from different angles followed by 3D image reconstruction—was developed to address this issue for light sheet microscopy based on fluorescence signal. In this study we applied this methodology to accomplish Multiview imaging with multiphoton microscopy based on fluorescence and additionally second harmonic signal from myosin and collagen. It was shown that isotropic resolution was achieved, the entirety of the sample was visualized, and interference artifacts were suppressed allowing clear visualization of collagen fibrils and myofibrils. This method can be applied to any scanning microscopy technique without microscope modifications. It can be used for imaging tissue and whole mount small organisms such as heart tissue, and zebrafish larva in 3D, label-free or stained, with at least threefold axial resolution improvement which can be significant for the accurate quantification of small 3D structures.

Neuronal plasticity allows an animal to respond to environmental changes by modulating its response to stimuli. In the honey bee (Apis mellifera), the biogenic amine octopamine plays a crucial role in appetitive odor learning, but little is known about how octopamine affects the brain. We investigated its effect in the antennal lobe, the first olfactory center in the brain, using calcium imaging to record background activity and odor responses before and after octopamine application. We show that octopamine increases background activity in olfactory output neurons, while reducing average calcium levels. Odor responses were modulated both upwards and downwards, with more odor response increases in glomeruli with negative or weak odor responses. Importantly, the octopamine effect was variable across glomeruli, odorants, odorant concentrations and animals, suggesting that the octopaminergic network is shaped by plasticity depending on an individual animal’s history and possibly other factors. Using RNA interference, we show that the octopamine receptor AmOA1 (homolog of the Drosophila OAMB receptor) is involved in the octopamine effect. We propose a network model in which octopamine receptors are plastic in their density and located on a subpopulation of inhibitory neurons in a disinhibitory pathway. This would improve odor-coding of behaviorally relevant, previously experienced odors.

A globally invasive form of the mosquito Aedes aegypti specializes in biting humans, making it an efficient disease vector 1 . Host-seeking female mosquitoes strongly prefer human odour over the odour of animals 2 , 3 , but exactly how they distinguish between the two is not known. Vertebrate odours are complex blends of volatile chemicals with many shared components 4 – 7 , making discrimination an interesting sensory coding challenge. Here we show that human and animal odours evoke activity in distinct combinations of olfactory glomeruli within the Ae. aegypti antennal lobe. One glomerulus in particular is strongly activated by human odour but responds weakly, or not at all, to animal odour. This human-sensitive glomerulus is selectively tuned to the long-chain aldehydes decanal and undecanal, which we show are consistently enriched in human odour and which probably originate from unique human skin lipids. Using synthetic blends, we further demonstrate that signalling in the human-sensitive glomerulus significantly enhances long-range host-seeking behaviour in a wind tunnel, recapitulating preference for human over animal odours. Our research suggests that animal brains may distil complex odour stimuli of innate biological relevance into simple neural codes and reveals targets for the design of next-generation mosquito-control strategies. Select chemical compounds enriched in human odour activate an olfactory glomerulus in the brain of Aedes aegypti mosquitoes, which strengthens host-seeking behaviour and helps explain their strong preference for biting humans.

Background The calcium-imaging technique allows us to record movies of brain activity in the antennal lobe of the fruitfly Drosophila melanogaster , a brain compartment dedicated to information about odors. Signal processing, e.g. with source separation techniques, can be slow on the large movie datasets. Method We have developed an approximate Principal Component Analysis (PCA) for fast dimensionality reduction. The method samples relevant pixels from the movies, such that PCA can be performed on a smaller matrix. Utilising a priori knowledge about the nature of the data, we minimise the risk of missing important pixels. Results Our method allows for fast approximate computation of PCA with adaptive resolution and running time. Utilising a priori knowledge about the data enables us to concentrate more biological signals in a small pixel sample than a general sampling method based on vector norms. Conclusions Fast dimensionality reduction with approximate PCA removes a computational bottleneck and leads to running time improvements for subsequent algorithms. Once in PCA space, we can efficiently perform source separation, e.g to detect biological signals in the movies or to remove artifacts.

Spermatogenesis, the complex developmental process of male germ cell proliferation, differentiation, and maturation, is the basis of male fertility. In the seminiferous tubules of the testes, spermatozoa are constantly generated from spermatogonial stem cells through a stereotyped sequence of divisions. The basic physiological principles, however, that control seminiferous tubule function remain poorly, if at all, defined. Here, we address cell type-specific seminiferous tubule signaling in vitro and in vivo. By monitoring changes in cellular Ca2+ concentration at high spatiotemporal resolution, we show that the three cell types that build the seminiferous epithelium-Sertoli, peritubular, and germ cells-each display unique Ca2+ signaling patterns. We reveal the underlying mechanisms and demonstrate that Sertoli cell Ca2+ signals are under gonadotropin regulation. Together, our experimental findings provide insights into seminiferous tubule signaling, its mechanistic basis, and its endocrine control.

Background Plants under herbivore attack release volatiles that attract natural enemies, and herbivores in turn avoid such plants. Whilst herbivore-induced plant volatile blends appeared to reduce the attractiveness of host plants to herbivores, the volatiles that are key in this process and particularly the way in which deterrence is coded in the olfactory system are largely unknown. Here we demonstrate that herbivore-induced cotton volatiles suppress orientation of the moth Spodoptera littoralis to host plants and mates. Results We found that ( E )-4,8-dimethyl-1,3,7-nonatriene (DMNT), an induced volatile, is key in herbivore deterrence: DMNT suppressed plant odour- and pheromone-induced behaviours. We then dissected the neurophysiological basis of this interaction. DMNT-responding glomeruli were also activated by other plant compounds, suggesting that S. littoralis possesses no segregated olfactory circuit dedicated exclusively to DMNT. Instead, DMNT suppressed responses to the main pheromone component, ( Z )-9-( E )-11-tetradecenyl acetate, and primarily to ( Z )-3-hexenyl acetate, a host plant attractant. Conclusion Our study shows that olfactory sensory inhibition, which has previously been reported without reference to an animal’s ecology, can be at the core of coding of ecologically relevant odours. As DMNT attracts natural enemies and deters herbivores, it may be useful in the development or enhancement of push-pull strategies for sustainable agriculture.

Cancer cells and non-cancer cells differ in their metabolism and they emit distinct volatile compound profiles, allowing to recognise cancer cells by their scent. Insect odorant receptors are excellent chemosensors with high sensitivity and a broad receptive range unmatched by current gas sensors. We thus investigated the potential of utilising the fruit fly's olfactory system to detect cancer cells. Using in vivo calcium imaging, we recorded an array of olfactory receptor neurons on the fruit fly's antenna. We performed multidimensional analysis of antenna responses, finding that cell volatiles from different cell types lead to characteristic response vectors. The distances between these response vectors are conserved across flies and can be used to discriminate healthy mammary epithelial cells from different types of breast cancer cells. This may expand the repertoire of clinical diagnostics and it is the first step towards electronic noses equipped with biological sensors, integrating artificial and biological olfaction.