More than double the fun with two-photon excitation microscopy.

For generations researchers have been observing the dynamic processes of life through the lens of a microscope. This has offered tremendous insights into biological phenomena that span multiple orders of time- and length-scales ranging from the pure magic of molecular reorganization at the membrane of immune cells, to cell migration and differentiation during development or wound healing. Standard fluorescence microscopy techniques offer glimpses at such processes in vitro, however, when applied in intact systems, they are challenged by reduced signal strengths and signal-to-noise ratios that result from deeper imaging. As a remedy, two-photon excitation (TPE) microscopy takes a special place, because it allows us to investigate processes in vivo, in their natural environment, even in a living animal. Here, we review the fundamental principles underlying TPE aimed at basic and advanced microscopy users interested in adopting TPE for intravital imaging. We focus on applications in neurobiology, present current trends towards faster, wider and deeper imaging, discuss the combination with photon counting technologies for metabolic imaging and spectroscopy, as well as highlight outstanding issues and drawbacks in development and application of these methodologies.

Artificial neural network identification of exercise expiratory flow-limitation in adults.

Identification of ventilatory constraint is a key objective of clinical exercise testing. Expiratory flow-limitation (EFL) is a well-known type of ventilatory constraint. However, EFL is difficult to measure, and commercial metabolic carts do not readily identify or quantify EFL. Deep machine learning might provide a new approach for identifying EFL. The objective of this study was to determine if a convolutional neural network (CNN) could accurately identify EFL during exercise in adults in whom baseline airway function varied from normal to mildly obstructed. 2931 spontaneous exercise flow-volume loops (eFVL) were placed within the baseline maximal expiratory flow-volume curves (MEFV) from 22 adults (15 M, 7 F; age, 32 yrs) in whom lung function varied from normal to mildly obstructed. Each eFVL was coded as EFL or non-EFL, where EFL was defined by eFVLs with expired airflow meeting or exceeding the MEFV curve. A CNN with seven hidden layers and a 2-neuron softmax output layer was used to analyze the eFVLs. Three separate analyses were conducted: (1) all subjects (n = 2931 eFVLs, [GRALL]), (2) subjects with normal spirometry (n = 1921 eFVLs [GRNORM]), (3) subjects with mild airway obstruction (n = 1010 eFVLs, [GRLOW]). The final output of the CNN was the probability of EFL or non-EFL in each eFVL, which is considered EFL if the probability exceeds 0.5 or 50%. Baseline forced expiratory volume in 1 s/forced vital capacity was 0.77 (94% predicted) in GRALL, 0.83 (100% predicted) in GRNORM, and 0.69 (83% predicted) in GRLOW. CNN model accuracy was 90.6, 90.5, and 88.0% in GRALL, GRNORM and GRLOW, respectively. Negative predictive value (NPV) was higher than positive predictive value (PPV) in GRNORM (93.5 vs. 78.2% for NPV vs. PPV). In GRLOW, PPV was slightly higher than NPV (89.5 vs. 84.5% for PPV vs. NPV). A CNN performed very well at identifying eFVLs with EFL during exercise. These findings suggest that deep machine learning could become a viable tool for identifying ventilatory constraint during clinical exercise testing.

VoDEx: a Python library for time annotation and management of volumetric functional imaging data.

SUMMARY: In functional imaging studies, accurately synchronizing the time course of experimental manipulations and stimulus presentations with resulting imaging data is crucial for analysis. Current software tools lack such functionality, requiring manual processing of the experimental and imaging data, which is error-prone and potentially non-reproducible. We present VoDEx, an open-source Python library that streamlines the data management and analysis of functional imaging data. VoDEx synchronizes the experimental timeline and events (e.g. presented stimuli, recorded behavior) with imaging data. VoDEx provides tools for logging and storing the timeline annotation, and enables retrieval of imaging data based on specific time-based and manipulation-based experimental conditions. AVAILABILITY AND IMPLEMENTATION: VoDEx is an open-source Python library and can be installed via the "pip install" command. It is released under a BSD license, and its source code is publicly accessible on GitHub (https://github.com/LemonJust/vodex). A graphical interface is available as a napari-vodex plugin, which can be installed through the napari plugins menu or using "pip install." The source code for the napari plugin is available on GitHub (https://github.com/LemonJust/napari-vodex). The software version at the time of submission is archived at Zenodo (version v1.0.18, https://zenodo.org/record/8061531).

VoDEx: a Python library for time annotation and management of volumetric functional imaging data.

In functional imaging studies, accurately synchronizing the time course of experimental manipulations and stimulus presentations with resulting imaging data is crucial for analysis. Current software tools lack such functionality, requiring manual processing of the experimental and imaging data, which is error-prone and potentially non-reproducible. We present VoDEx, an open-source Python library that streamlines the data management and analysis of functional imaging data. VoDEx synchronizes the experimental timeline and events (eg. presented stimuli, recorded behavior) with imaging data. VoDEx provides tools for logging and storing the timeline annotation, and enables retrieval of imaging data based on specific time-based and manipulation-based experimental conditions. Availability and Implementation: VoDEx is an open-source Python library and can be installed via the "pip install" command. It is released under a BSD license, and its source code is publicly accessible on GitHub https://github.com/LemonJust/vodex. A graphical interface is available as a napari-vodex plugin, which can be installed through the napari plugins menu or using "pip install." The source code for the napari plugin is available on GitHub https://github.com/LemonJust/napari-vodex.

Effect of exercise-induced bronchoconstriction on the configuration of the maximal expiratory flow-volume curve in adults with asthma.

We determined the effect of exercise-induced bronchoconstriction (EIB) on the shape of the maximal expiratory flow-volume (MEFV) curve in asthmatic adults. The slope-ratio index (SR) was used to quantitate the shape of the MEFV curve. We hypothesized that EIB would be accompanied by increases in SR and thus increased curvilinearity of the MEFV curve. Adult asthmatic ( n  = 10) and non-asthmatic control subjects ( n  = 9) cycled for 6-8 min at 85% of peak power. Following exercise, subjects remained on the ergometer and performed a maximal forced exhalation every 2 min for a total 20 min. In each MEFV curve, the slope-ratio index (SR) was calculated in 1% volume increments beginning at peak expiratory flow (PEF) and ending at 20% of forced vital capacity (FVC). Baseline spirometry was lower in asthmatics compared to control subjects (FEV1 % predicted, 89.1 ± 14.3 vs. 96.5 ± 12.2% [SD] in asthma vs. control; p  < 0.05). In asthmatic subjects, post-exercise FEV1 decreased by 29.9 ± 13.2% from baseline (3.48 ± 0.74 and 2.24 ± 0.59 [SD] L for baseline and post-exercise nadir; p  < 0.001). At baseline and at all timepoints after exercise, average SR between 80 and 20% of FVC was larger in asthmatic than control subjects (1.48 ± 0.02 vs. 1.23 ± 0.02 [SD] for asthma vs. control; p < 0.005). This averaged SR did not change after exercise in either subject group. In contrast, post-exercise SR between PEF and 75% of FVC was increased from baseline in subjects with asthma, suggesting that airway caliber heterogeneity increases with EIB. These findings suggest that the SR-index might provide useful information on the physiology of acute airway narrowing that complements traditional spirometric measures.

Extended depth-of-field light-sheet microscopy improves imaging of large volumes at high numerical aperture.

Light-sheet microscopes must compromise among field of view, optical sectioning, resolution, and detection efficiency. High-numerical-aperture (NA) detection objective lenses provide higher resolution, but their narrow depth of field inefficiently captures the fluorescence signal generated throughout the thickness of the illumination light sheet when imaging large volumes. Here, we present ExD-SPIM (extended depth-of-field selective-plane illumination microscopy), an improved light-sheet microscopy strategy that solves this limitation by extending the depth of field (DOF) of high-NA detection objectives to match the thickness of the illumination light sheet. This extension of the DOF uses a phase mask to axially stretch the point-spread function of the objective lens while largely preserving lateral resolution. This matching of the detection DOF to the illumination-sheet thickness increases the total fluorescence collection, reduces the background, and improves the overall signal-to-noise ratio (SNR), as shown by numerical simulations, imaging of bead phantoms, and imaging living animals. In comparison to conventional light sheet imaging with low-NA detection that yields equivalent DOF, the results show that ExD-SPIM increases the SNR by more than threefold and dramatically reduces the rate of photobleaching. Compared to conventional high-NA detection, ExD-SPIM improves the signal sensitivity and volumetric coverage of whole-brain activity imaging, increasing the number of detected neurons by over a third.

Quantity as a Fish Views It: Behavior and Neurobiology.

An ability to estimate quantities, such as the number of conspecifics or the size of a predator, has been reported in vertebrates. Fish, in particular zebrafish, may be instrumental in advancing the understanding of magnitude cognition. We review here the behavioral studies that have described the ecological relevance of quantity estimation in fish and the current status of the research aimed at investigating the neurobiological bases of these abilities. By combining behavioral methods with molecular genetics and calcium imaging, the involvement of the retina and the optic tectum has been documented for the estimation of continuous quantities in the larval and adult zebrafish brain, and the contributions of the thalamus and the dorsal-central pallium for discrete magnitude estimation in the adult zebrafish brain. Evidence for basic circuitry can now be complemented and extended to research that make use of transgenic lines to deepen our understanding of quantity cognition at genetic and molecular levels.

Single-objective selective-volume illumination microscopy enables high-contrast light-field imaging.

The performance of light-field microscopy is improved by selectively illuminating the relevant subvolume of the specimen with a second objective lens. Here we advance this approach to a single-objective geometry, using an oblique one-photon illumination path or two-photon illumination to accomplish selective-volume excitation. The elimination of the second orthogonally oriented objective to selectively excite the volume of interest simplifies specimen mounting; yet, this single-objective approach still reduces the out-of-volume background, resulting in improvements in image contrast, effective resolution, and volume reconstruction quality. We validate our new, to the best of our knowledge, approach through imaging live developing zebrafish, demonstrating the technology's ability to capture imaging data from large volumes synchronously with high contrast while remaining compatible with standard microscope sample mounting.

A Novel Gene Controlling the Timing of Courtship Initiation in Drosophila melanogaster.

Over the past 35 years, developmental geneticists have made impressive progress toward an understanding of how genes specify morphology and function, particularly as they relate to the specification of each physical component of an organism. In the last 20 years, male courtship behavior in Drosophila melanogaster has emerged as a robust model system for the study of genetic specification of behavior. Courtship behavior is both complex and innate, and a single gene, fruitless (fru), is both necessary and sufficient for all aspects of the courtship ritual. Typically, loss of male-specific Fruitless protein function results in male flies that perform the courtship ritual incorrectly, slowly, or not at all. Here we describe a novel requirement for fru: we have identified a group of cells in which male Fru proteins are required to reduce the speed of courtship initiation. In addition, we have identified a gene, Trapped in endoderm 1 (Tre1), which is required in these cells for normal courtship and mating behavior. Tre1 encodes a G-protein-coupled receptor required for establishment of cell polarity and cell migration and has previously not been shown to be involved in courtship behavior. We describe the results of feminization of the Tre1-expressing neurons, as well as the effects on courtship behavior of mutation of Tre1. In addition, we show that Tre1 is expressed in a sexually dimorphic pattern in the central and peripheral nervous systems and investigate the role of the Tre1 cells in mate identification.

Developmental ethanol exposure leads to dysregulation of lipid metabolism and oxidative stress in Drosophila.

Ethanol exposure during development causes an array of developmental abnormalities, both physiological and behavioral. In mammals, these abnormalities are collectively known as fetal alcohol effects (FAE) or fetal alcohol spectrum disorder (FASD). We have established a Drosophila melanogaster model of FASD and have previously shown that developmental ethanol exposure in flies leads to reduced expression of insulin-like peptides (dILPs) and their receptor. In this work, we link that observation to dysregulation of fatty acid metabolism and lipid accumulation. Further, we show that developmental ethanol exposure in Drosophila causes oxidative stress, that this stress is a primary cause of the developmental lethality and delay associated with ethanol exposure, and, finally, that one of the mechanisms by which ethanol increases oxidative stress is through abnormal fatty acid metabolism. These data suggest a previously uncharacterized mechanism by which ethanol causes the symptoms associated with FASD.