Ecologically sustainable benchmarking of AI models for histopathology.

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.

Modeling the Temperature-Dependent Size Change of Polydisperse Nano-objects using a Deep Generative Model.

Modern microscopy techniques can be used to investigate soft nano-objects at the nanometer scale. However, time-consuming microscopy measurements combined with low numbers of observable polydisperse objects often limit the statistics. We propose a method for identifying the most representative objects from their respective point clouds.

A revised conceptual framework for mouse vomeronasal pumping and stimulus sampling.

The physiological performance of any sensory organ is determined by its anatomy and physical properties. Consequently, complex sensory structures with elaborate features have evolved to optimize stimulus detection. Understanding these structures and their physical nature forms the basis for mechanistic insights into sensory function.

The intra- and inter-rater reproducibility of bone level measurements at strategic mini-implants using dental panoramic radiography.

Objectives: This experimental study focused on the intra- and inter-rater reproducibility of vertical bone level (VBL) measurements at strategic mini-implants (MI) using digital panoramic radiographs (PR).

Study Design: VBLs of 152 MIs for removable partial denture stabilization at 50 randomly chosen PRs from a clinical trial were digitally evaluated by three ratters. Rater deviations exceeding 0.

Rewarding Capacity of Optogenetically Activating a Giant GABAergic Central-Brain Interneuron in Larval .

Larvae of the fruit fly are a powerful study case for understanding the neural circuits underlying behavior. Indeed, the numerical simplicity of the larval brain has permitted the reconstruction of its synaptic connectome, and genetic tools for manipulating single, identified neurons allow neural circuit function to be investigated with relative ease and precision. We focus on one of the most complex neurons in the brain of the larva (of either sex), the GABAergic anterior paired lateral neuron (APL).

High-throughput phenotyping of nematode cysts.

The beet cyst nematode 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.

Learning to Segment Fine Structures Under Image-Level Supervision With an Application to Nematode Segmentation.

Image segmentation models trained only with image-level labels have become increasingly popular as they require significantly less annotation effort than models trained with scribble, bounding box or pixel-wise annotations. While methods utilizing image-level labels achieve promising performance for the segmentation of larger-scale objects, they perform less well for the fine structures frequently encountered in biological images. In order to address this performance gap, we propose a deep network architecture based on two key principles, Global Weighted Pooling (GWP) and segmentation refinement by low-level image cues, that, together, make segmentation of fine structures possible.

Mosquito brains encode unique features of human odour to drive host seeking.

A globally invasive form of the mosquito Aedes aegypti specializes in biting humans, making it an efficient disease vector. Host-seeking female mosquitoes strongly prefer human odour over the odour of animals, but exactly how they distinguish between the two is not known. Vertebrate odours are complex blends of volatile chemicals with many shared components, making discrimination an interesting sensory coding challenge.

Multiview deconvolution approximation multiphoton microscopy of tissues and zebrafish larvae.

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.

ATP activation of peritubular cells drives testicular sperm transport.

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.

Identification of Dopaminergic Neurons That Can Both Establish Associative Memory and Acutely Terminate Its Behavioral Expression.

An adaptive transition from exploring the environment in search of vital resources to exploiting these resources once the search was successful is important to all animals. Here we study the neuronal circuitry that allows larval of either sex to negotiate this exploration-exploitation transition. We do so by combining Pavlovian conditioning with high-resolution behavioral tracking, optogenetic manipulation of individually identified neurons, and EM data-based analyses of synaptic organization.

Instance Segmentation of Nematode Cysts in Microscopic Images of Soil Samples.

Nematodes are plant parasites that cause damage to crops. In order to quantify nematode infestation based on soil samples, we propose an instance segmentation method that will serve as the basis of automatic quantitative analysis. We consider light microscopic images of cluttered object collections as they occur in realistic soil samples.

Deformation of Microgels at Solid-Liquid Interfaces Visualized in Three-Dimension.

Solid-liquid interfaces play an important role for functional devices. Hence, a detailed understanding of the interaction of soft matter objects with solid supports and of the often concomitant structural deformations is of great importance. We address this topic in a combined experimental and simulation approach.

Normalizing brain activity across individuals using functional reference mapping.

Neural activity can be mapped across individuals using brain atlases, but when spatial relationships are not equal, these techniques collapse. We map activity across individuals using functional registration, based on physiological responses to predetermined reference stimuli. Data from several individuals are integrated into a common multidimensional stimulus space, where dimensionality and axes are defined by these reference stimuli.

larvalign: Aligning Gene Expression Patterns from the Larval Brain of Drosophila melanogaster.

The larval brain of the fruit fly Drosophila melanogaster is a small, tractable model system for neuroscience. Genes for fluorescent marker proteins can be expressed in defined, spatially restricted neuron populations. Here, we introduce the methods for 1) generating a standard template of the larval central nervous system (CNS), 2) spatial mapping of expression patterns from different larvae into a reference space defined by the standard template.

A herbivore-induced plant volatile interferes with host plant and mate location in moths through suppression of olfactory signalling pathways.

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.

The looks of an odour--visualising neural odour response patterns in real time.

Background: Calcium imaging in insects reveals the neural response to odours, both at the receptor level on the antenna and in the antennal lobe, the first stage of olfactory information processing in the brain. Changes of intracellular calcium concentration in response to odour presentations can be observed by employing calcium-sensitive, fluorescent dyes. The response pattern across all recorded units is characteristic for the odour.

Signal extraction from movies of honeybee brain activity: the ImageBee plugin for KNIME.

Background: In the antennal lobe, a dedicated olfactory center of the honeybee brain, odours are encoded as activity patterns of coding units, the so-called glomeruli. Optical imaging with calcium-sensitive dyes allows us to record these activity patterns and to gain insight into olfactory information processing in the brain.

Method: We introduce ImageBee, a plugin for the data analysis platform KNIME.

More than apples and oranges--detecting cancer with a fruit fly's antenna.

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.

Octopamine modulates activity of neural networks in the honey bee antennal lobe.

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.

Keeping their distance? Odor response patterns along the concentration range.

We investigate the interplay of odor identity and concentration coding in the antennal lobe (AL) of the honeybee Apis mellifera. In this primary olfactory center of the honeybee brain, odors are encoded by the spatio-temporal response patterns of olfactory glomeruli. With rising odor concentration, further glomerular responses are recruited into the patterns, which affects distances between the patterns.

Fast PCA for processing calcium-imaging data from the brain of Drosophila melanogaster.

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.

Integrating heterogeneous odor response data into a common response model: A DoOR to the complete olfactome.

We have developed a new computational framework for merging odor response data sets from heterogeneous studies, creating a consensus metadatabase, the database of odor responses (DoOR). As a result, we obtained a functional atlas of all available odor responses in Drosophila melanogaster. Both the program and the data set are freely accessible and downloadable on the Internet (http://neuro.

EDISA: extracting biclusters from multiple time-series of gene expression profiles.

Background: Cells dynamically adapt their gene expression patterns in response to various stimuli. This response is orchestrated into a number of gene expression modules consisting of co-regulated genes. A growing pool of publicly available microarray datasets allows the identification of modules by monitoring expression changes over time.