Neural mechanisms to incorporate visual counterevidence in self-movement estimation

In selecting appropriate behaviors, animals should weigh sensory evidence both for and against specific beliefs about the world. For instance, animals measure optic flow to estimate and control their own rotation. However, existing models of flow detection can be spuriously triggered by visual motion created by objects moving in the world. Here, we show that stationary patterns on the retina, which constitute evidence against observer rotation, suppress inappropriate stabilizing rotational behavior in the fruit fly Drosophila. In silico experiments show that artificial neural networks (ANNs) that are optimized to distinguish observer movement from external object motion similarly detect stationarity and incorporate negative evidence. Employing neural measurements and genetic manipulations, we identified components of the circuitry for stationary pattern detection, which runs parallel to the fly's local motion and optic-flow detectors. Our results show how the fly brain incorporates negative evidence to improve heading stability, exemplifying how a compact brain exploits geometrical constraints of the visual world.

Direct comparison reveals algorithmic similarities in fly and mouse visual motion detection

Evolution has equipped vertebrates and invertebrates with neural circuits that selectively encode visual motion. While similarities in the computations performed by these circuits in mouse and fruit fly have been noted, direct experimental comparisons have been lacking. Because molecular mechanisms and neuronal morphology in the two species are distinct, we directly compared motion encoding in these two species at the algorithmic level, using matched stimuli and focusing on a pair of analogous neurons, the mouse ON starburst amacrine cell (ON SAC) and Drosophila T4 neurons. We find that the cells share similar spatiotemporal receptive field structures, sensitivity to spatiotemporal correlations, and tuning to sinusoidal drifting gratings, but differ in their responses to apparent motion stimuli. Both neuron types showed a response to summed sinusoids that deviates from models for motion processing in these cells, underscoring the similarities in their processing and identifying response features that remain to be explained.

Long-timescale anti-directional rotation in Drosophila optomotor behavior

Locomotor movements cause visual images to be displaced across the eye, a retinal slip that is counteracted by stabilizing reflexes in many animals. In insects, optomotor turning causes the animal to turn in the direction of rotating visual stimuli, thereby reducing retinal slip and stabilizing trajectories through the world. This behavior has formed the basis for extensive dissections of motion vision. Here, we report that under certain stimulus conditions, two Drosophila species, including the widely studied Drosophila melanogaster, can suppress and even reverse the optomotor turning response over several seconds. Such 'anti-directional turning' is most strongly evoked by long-lasting, high-contrast, slow-moving visual stimuli that are distinct from those that promote syn-directional optomotor turning. Anti-directional turning, like the syn-directional optomotor response, requires the local motion detecting neurons T4 and T5. A subset of lobula plate tangential cells, CH cells, show involvement in these responses. Imaging from a variety of direction-selective cells in the lobula plate shows no evidence of dynamics that match the behavior, suggesting that the observed inversion in turning direction emerges downstream of the lobula plate. Further, anti-directional turning declines with age and exposure to light. These results show that Drosophila optomotor turning behaviors contain rich, stimulus-dependent dynamics that are inconsistent with simple reflexive stabilization responses.

Neural mechanisms to incorporate visual counterevidence in self motion estimation

In selecting appropriate behaviors, animals should weigh sensory evidence both for and against specific beliefs about the world. For instance, animals measure optic flow to estimate and control their own rotation. However, existing models of flow detection can confuse the movement of external objects with genuine self motion. Here, we show that stationary patterns on the retina, which constitute negative evidence against self rotation, are used by the fruit fly Drosophila to suppress inappropriate stabilizing rotational behavior. In silico experiments show that artificial neural networks optimized to distinguish self and world motion similarly detect stationarity and incorporate negative evidence. Employing neural measurements and genetic manipulations, we identified components of the circuitry for stationary pattern detection, which runs parallel to the fly's motion- and optic flow-detectors. Our results exemplify how the compact brain of the fly incorporates negative evidence to improve heading stability, exploiting geometrical constraints of the visual world.

Long timescale anti-directional rotation in Drosophila optomotor behavior

Locomotor movements cause visual images to be displaced across the eye, a retinal slip that is counteracted by stabilizing reflexes in many animals. In insects, optomotor turning causes the animal to turn in the direction of rotating visual stimuli, thereby reducing retinal slip and stabilizing trajectories through the world. This behavior has formed the basis for extensive dissections of motion vision. Here, we report that under certain stimulus conditions, two Drosophila species, including the widely studied D. melanogaster, can suppress and even reverse the optomotor turning response over several seconds. Such "anti-directional turning" is most strongly evoked by long-lasting, high-contrast, slow-moving visual stimuli that are distinct from those that promote syn-directional optomotor turning. Anti-directional turning, like the syn-directional optomotor response, requires the local motion detecting neurons T4 and T5. A subset of lobula plate tangential cells, CH cells, show involvement in these responses. Imaging from a variety of direction-selective cells in the lobula plate shows no evidence of dynamics that match the behavior, suggesting that the observed inversion in turning direction emerges downstream of the lobula plate. Further, anti-directional turning declines with age and exposure to light. These results show that Drosophila optomotor turning behaviors contain rich, stimulus-dependent dynamics that are inconsistent with simple reflexive stabilization responses.

Odour motion sensing enhances navigation of complex plumes

Odour plumes in the wild are spatially complex and rapidly fluctuating structures carried by turbulent airflows^1-4. To successfully navigate plumes in search of food and mates, insects must extract and integrate multiple features of the odour signal, including odour identity⁵, intensity⁶ and timing^6-12. Effective navigation requires balancing these multiple streams of olfactory information and integrating them with other sensory inputs, including mechanosensory and visual cues^9,12,13. Studies dating back a century have indicated that, of these many sensory inputs, the wind provides the main directional cue in turbulent plumes, leading to the longstanding model of insect odour navigation as odour-elicited upwind motion^6,8-12,14,15. Here we show that Drosophila melanogaster shape their navigational decisions using an additional directional cue-the direction of motion of odours-which they detect using temporal correlations in the odour signal between their two antennae. Using a high-resolution virtual-reality paradigm to deliver spatiotemporally complex fictive odours to freely walking flies, we demonstrate that such odour-direction sensing involves algorithms analogous to those in visual-direction sensing¹⁶. Combining simulations, theory and experiments, we show that odour motion contains valuable directional information that is absent from the airflow alone, and that both Drosophila and virtual agents are aided by that information in navigating naturalistic plumes. The generality of our findings suggests that odour-direction sensing may exist throughout the animal kingdom and could improve olfactory robot navigation in uncertain environments.

Excitatory and inhibitory neural dynamics jointly tune motion detection

Neurons integrate excitatory and inhibitory signals to produce their outputs, but the role of input timing in this integration remains poorly understood. Motion detection is a paradigmatic example of this integration, since theories of motion detection rely on different delays in visual signals. These delays allow circuits to compare scenes at different times to calculate the direction and speed of motion. Different motion detection circuits have different velocity sensitivity, but it remains untested how the response dynamics of individual cell types drive this tuning. Here, we sped up or slowed down specific neuron types in Drosophila's motion detection circuit by manipulating ion channel expression. Altering the dynamics of individual neuron types upstream of motion detectors increased their sensitivity to fast or slow visual motion, exposing distinct roles for excitatory and inhibitory dynamics in tuning directional signals, including a role for the amacrine cell CT1. A circuit model constrained by functional data and anatomy qualitatively reproduced the observed tuning changes. Overall, these results reveal how excitatory and inhibitory dynamics together tune a canonical circuit computation.

Feature maps: How the insect visual system organizes information

A new study explores how a population of neurons in the insect brain responds to different features of visual scenes and discovers an unusual topographic map that organizes the information they encode.

Shallow neural networks trained to detect collisions recover features of visual loom-selective neurons

Animals have evolved sophisticated visual circuits to solve a vital inference problem: detecting whether or not a visual signal corresponds to an object on a collision course. Such events are detected by specific circuits sensitive to visual looming, or objects increasing in size. Various computational models have been developed for these circuits, but how the collision-detection inference problem itself shapes the computational structures of these circuits remains unknown. Here, inspired by the distinctive structures of LPLC2 neurons in the visual system of Drosophila, we build anatomically-constrained shallow neural network models and train them to identify visual signals that correspond to impending collisions. Surprisingly, the optimization arrives at two distinct, opposing solutions, only one of which matches the actual dendritic weighting of LPLC2 neurons. Both solutions can solve the inference problem with high accuracy when the population size is large enough. The LPLC2-like solutions reproduces experimentally observed LPLC2 neuron responses for many stimuli, and reproduces canonical tuning of loom sensitive neurons, even though the models are never trained on neural data. Thus, LPLC2 neuron properties and tuning are predicted by optimizing an anatomically-constrained neural network to detect impending collisions. More generally, these results illustrate how optimizing inference tasks that are important for an animal's perceptual goals can reveal and explain computational properties of specific sensory neurons.

Predicting individual neuron responses with anatomically constrained task optimization

Artificial neural networks trained to solve sensory tasks can develop statistical representations that match those in biological circuits. However, it remains unclear whether they can reproduce properties of individual neurons. Here, we investigated how artificial networks predict individual neuron properties in the visual motion circuits of the fruit fly Drosophila. We trained anatomically constrained networks to predict movement in natural scenes, solving the same inference problem as fly motion detectors. Units in the artificial networks adopted many properties of analogous individual neurons, even though they were not explicitly trained to match these properties. Among these properties was the split into ON and OFF motion detectors, which is not predicted by classical motion detection models. The match between model and neurons was closest when models were trained to be robust to noise. These results demonstrate how anatomical, task, and noise constraints can explain properties of individual neurons in a small neural network.

A metabolic daylength measurement system mediates winter photoperiodism in plants

Plants have served as a preeminent study system for photoperiodism due to their propensity to flower in concordance with the seasons. A nearly singular focus on understanding photoperiodic flowering has prevented the discovery of other photoperiod measuring systems necessary for vegetative health. Here, we use bioinformatics to identify photoperiod-induced genes in Arabidopsis. We show that one, PP2-A13, is expressed exclusively in, and required for, plant fitness in short, winter-like photoperiods. We create a real-time photoperiod reporter, using the PP2-A13 promoter driving luciferase, and show that photoperiodic regulation is independent of the canonical CO/FT mechanism for photoperiodic flowering. We then reveal that photosynthesis combines with circadian-clock-controlled starch production to regulate cellular sucrose levels to control photoperiodic expression of PP2-A13. This work demonstrates the existence of a photoperiod measuring system housed in the metabolic network of plants that functions to control seasonal cellular health.

Amylase quantification in the terminal Ileum following formation of an Ileostomy

Amylase is elevated in the foregut and has been used to confirm anastomotic integrity after pancreatic surgery. The physiological activity of pancreatic enzymes in the ileum has been studied in healthy volunteers but not quantitated with the simple and readily available amylase measurements employed with serum tests. We aim to quantitate the levels of amylase in the terminal ileum. This was a prospective, non-randomised, non-blinded, consecutive cohort study conducted at the Royal Brisbane and Women's Hospital. Consecutive patients undergoing routine surgery with an ileostomy were invited to participate in the study. Ileostomy effluent was collected and analysed daily for the first 5 post-operative days. This validation cohort included 8 males and 3 females, with a mean age of 49 years. Median daily amylase levels ranged from 4470 U/L to 23,000 U/L, with no specimens falling within the laboratory serum reference range of 40 to 130 U/L. Two specimens were not available on day one post-operative due to complete ileus. The sample size of 11 patients is small but was considered sufficient given that 55 effluent specimens were anticipated for analysis. Amylase levels remain highly elevated as the enzyme transits through the length of the small intestine and measured in the terminal ileum, and can be readily quantitated by the existing testing methodology routinely available.

Walking Drosophila navigate complex plumes using stochastic decisions biased by the timing of odor encounters

How insects navigate complex odor plumes, where the location and timing of odor packets are uncertain, remains unclear. Here we imaged complex odor plumes simultaneously with freely-walking flies, quantifying how behavior is shaped by encounters with individual odor packets. We found that navigation was stochastic and did not rely on the continuous modulation of speed or orientation. Instead, flies turned stochastically with stereotyped saccades, whose direction was biased upwind by the timing of prior odor encounters, while the magnitude and rate of saccades remained constant. Further, flies used the timing of odor encounters to modulate the transition rates between walks and stops. In more regular environments, flies continuously modulate speed and orientation, even though encounters can still occur randomly due to animal motion. We find that in less predictable environments, where encounters are random in both space and time, walking flies navigate with random walks biased by encounter timing.

Mechanism for analogous illusory motion perception in flies and humans

Visual motion detection is one of the most important computations performed by visual circuits. Yet, we perceive vivid illusory motion in stationary, periodic luminance gradients that contain no true motion. This illusion is shared by diverse vertebrate species, but theories proposed to explain this illusion have remained difficult to test. Here, we demonstrate that in the fruit fly Drosophila, the illusory motion percept is generated by unbalanced contributions of direction-selective neurons' responses to stationary edges. First, we found that flies, like humans, perceive sustained motion in the stationary gradients. The percept was abolished when the elementary motion detector neurons T4 and T5 were silenced. In vivo calcium imaging revealed that T4 and T5 neurons encode the location and polarity of stationary edges. Furthermore, our proposed mechanistic model allowed us to predictably manipulate both the magnitude and direction of the fly's illusory percept by selectively silencing either T4 or T5 neurons. Interestingly, human brains possess the same mechanistic ingredients that drive our model in flies. When we adapted human observers to moving light edges or dark edges, we could manipulate the magnitude and direction of their percepts as well, suggesting that mechanisms similar to the fly's may also underlie this illusion in humans. By taking a comparative approach that exploits Drosophila neurogenetics, our results provide a causal, mechanistic account for a long-known visual illusion. These results argue that this illusion arises from architectures for motion detection that are shared across phyla.

A minimal synaptic model for direction selective neurons in Drosophila

Visual motion estimation is a canonical neural computation. In Drosophila, recent advances have identified anatomic and functional circuitry underlying direction-selective computations. Models with varying levels of abstraction have been proposed to explain specific experimental results but have rarely been compared across experiments. Here we use the wealth of available anatomical and physiological data to construct a minimal, biophysically inspired synaptic model for Drosophila’s first-order direction-selective T4 cells. We show how this model relates mathematically to classical models of motion detection, including the Hassenstein-Reichardt correlator model. We used numerical simulation to test how well this synaptic model could reproduce measurements of T4 cells across many datasets and stimulus modalities. These comparisons include responses to sinusoid gratings, to apparent motion stimuli, to stochastic stimuli, and to natural scenes. Without fine-tuning this model, it sufficed to reproduce many, but not all, response properties of T4 cells. Since this model is flexible and based on straightforward biophysical properties, it provides an extensible framework for developing a mechanistic understanding of T4 neural response properties. Moreover, it can be used to assess the sufficiency of simple biophysical mechanisms to describe features of the direction-selective computation and identify where our understanding must be improved.

Anastomotic leak does not affect long-term and longitudinal functional outcomes after ileal pouch surgery for ulcerative colitis when managed aggressively

BACKGROUND

Ileal pouch-anal anastomosis (IPAA) is an effective surgical alternative to a permanent ileostomy following proctocolectomy in patients with ulcerative colitis (UC). Anastomotic leakage (AL) is a serious postoperative complication of an intestinal anastomosis that is associated with increased morbidity and mortality. The aim of this study was to evaluate the longitudinal long-term functional outcomes of patients who had IPAA that was complicated by AL.

METHODS

A retrospective longitudinal cohort study was performed of patients who had an IPAA procedure at a tertiary referral centre and a metropolitan private centre in Australia, over a 14-year period (October 2003-October 2017). The long-term functional outcome was assessed using objective clinical measures such as the number of bowel motions during the day and overnight, ability to defer defaecation and the presence of faecal incontinence, and repeated at annual intervals.

RESULTS

A total of 138 patients [mean age 38.5 (± 16.9) years, 72 males] satisfied the inclusion criteria. AL was diagnosed in 14 (10%) patients [mean age 38.8 (± 17) years, 10 males], 11 (79%) of which were managed with surgery. The median bowel motion frequency during the day and overnight remained stable over a median of 62 (28-91) months follow-up, with no significant difference between those who had AL or not (p = 0.6, p = 0.1 respectively). The incidence of faecal incontinence remained low, and the majority of patients in both groups were able to defer defaecation for more than 60 min. Six patients (4.3%) had their pouch excised.

CONCLUSIONS

There is no statistical difference in longitudinal function between patients who experienced AL after IPAA surgery for UC compared with those who did not. Therefore, an acute AL does not negatively impact long-term functional outcomes in IPAA patients.

Object-Displacement-Sensitive Visual Neurons Drive Freezing in Drosophila

Visual systems are often equipped with neurons that detect small moving objects, which may represent prey, predators, or conspecifics. Although the processing properties of those neurons have been studied in diverse organisms, links between the proposed algorithms and animal behaviors or circuit mechanisms remain elusive. Here, we have investigated behavioral function, computational algorithm, and neurochemical mechanisms of an object-selective neuron, LC11, in Drosophila. With genetic silencing and optogenetic activation, we show that LC11 is necessary for a visual object-induced stopping behavior in walking flies, a form of short-term freezing, and its activity can promote stopping. We propose a new quantitative model for small object selectivity based on the physiology and anatomy of LC11 and its inputs. The model accurately reproduces LC11 responses by pooling fast-adapting, tightly size-tuned inputs. Direct visualization of neurotransmitter inputs to LC11 confirmed the model conjectures about upstream processing. Our results demonstrate how adaptation can enhance selectivity for behaviorally relevant, dynamic visual features.

Dermal Adipocyte Lipolysis and Myofibroblast Conversion Are Required for Efficient Skin Repair

Mature adipocytes store fatty acids and are a common component of tissue stroma. Adipocyte function in regulating bone marrow, skin, muscle, and mammary gland biology is emerging, but the role of adipocyte-derived lipids in tissue homeostasis and repair is poorly understood. Here, we identify an essential role for adipocyte lipolysis in regulating inflammation and repair after injury in skin. Genetic mouse studies revealed that dermal adipocytes are necessary to initiate inflammation after injury and promote subsequent repair. We find through histological, ultrastructural, lipidomic, and genetic experiments in mice that adipocytes adjacent to skin injury initiate lipid release necessary for macrophage inflammation. Tamoxifen-inducible genetic lineage tracing of mature adipocytes and single-cell RNA sequencing revealed that dermal adipocytes alter their fate and generate ECM-producing myofibroblasts within wounds. Thus, adipocytes regulate multiple aspects of repair and may be therapeutic for inflammatory diseases and defective wound healing associated with aging and diabetes.

Spatiotemporally precise optogenetic activation of sensory neurons in freely walking Drosophila

Previous work has characterized how walking Drosophila coordinate the movements of individual limbs (DeAngelis et al., 2019). To understand the circuit basis of this coordination, one must characterize how sensory feedback from each limb affects walking behavior. However, it has remained difficult to manipulate neural activity in individual limbs of freely moving animals. Here, we demonstrate a simple method for optogenetic stimulation with body side-, body segment-, and limb-specificity that does not require real-time tracking. Instead, we activate at random, precise locations in time and space and use post hoc analysis to determine behavioral responses to specific activations. Using this method, we have characterized limb coordination and walking behavior in response to transient activation of mechanosensitive bristle neurons and sweet-sensing chemoreceptor neurons. Our findings reveal that activating these neurons has opposite effects on turning, and that activations in different limbs and body regions produce distinct behaviors.

Heterogeneous Temporal Contrast Adaptation in Drosophila Direction-Selective Circuits

In visual systems, neurons adapt both to the mean light level and to the range of light levels, or the contrast. Contrast adaptation has been studied extensively, but it remains unclear how it is distributed among neurons in connected circuits, and how early adaptation affects subsequent computations. Here, we investigated temporal contrast adaptation in neurons across Drosophila's visual motion circuitry. Several ON-pathway neurons showed strong adaptation to changes in contrast over time. One of these neurons, Mi1, showed almost complete adaptation on fast timescales, and experiments ruled out several potential mechanisms for its adaptive properties. When contrast adaptation reduced the gain in ON-pathway cells, it was accompanied by decreased motion responses in downstream direction-selective cells. Simulations show that contrast adaptation can substantially improve motion estimates in natural scenes. The benefits are larger for ON-pathway adaptation, which helps explain the heterogeneous distribution of contrast adaptation in these circuits.

Using slow frame rate imaging to extract fast receptive fields

In functional imaging, large numbers of neurons are measured during sensory stimulation or behavior. This data can be used to map receptive fields that describe neural associations with stimuli or with behavior. The temporal resolution of these receptive fields has traditionally been limited by image acquisition rates. However, even when acquisitions scan slowly across a population of neurons, individual neurons may be measured at precisely known times. Here, we apply a method that leverages the timing of neural measurements to find receptive fields with temporal resolutions higher than the image acquisition rate. We use this temporal super-resolution method to resolve fast voltage and glutamate responses in visual neurons in Drosophila and to extract calcium receptive fields from cortical neurons in mammals. We provide code to easily apply this method to existing datasets. This method requires no specialized hardware and can be used with any optical indicator of neural activity.

Asymmetric ON-OFF processing of visual motion cancels variability induced by the structure of natural scenes

Animals detect motion using a variety of visual cues that reflect regularities in the natural world. Experiments in animals across phyla have shown that motion percepts incorporate both pairwise and triplet spatiotemporal correlations that could theoretically benefit motion computation. However, it remains unclear how visual systems assemble these cues to build accurate motion estimates. Here, we used systematic behavioral measurements of fruit fly motion perception to show how flies combine local pairwise and triplet correlations to reduce variability in motion estimates across natural scenes. By generating synthetic images with statistics controlled by maximum entropy distributions, we show that the triplet correlations are useful only when images have light-dark asymmetries that mimic natural ones. This suggests that asymmetric ON-OFF processing is tuned to the particular statistics of natural scenes. Since all animals encounter the world's light-dark asymmetries, many visual systems are likely to use asymmetric ON-OFF processing to improve motion estimation.

The manifold structure of limb coordination in walking Drosophila

Terrestrial locomotion requires animals to coordinate their limb movements to efficiently traverse their environment. While previous studies in hexapods have reported that limb coordination patterns can vary substantially, the structure of this variability is not yet well understood. Here, we characterized the symmetric and asymmetric components of variation in walking kinematics in the genetic model organism Drosophila. We found that Drosophila use a single continuum of coordination patterns without evidence for preferred configurations. Spontaneous symmetric variability was associated with modulation of a single control parameter-stance duration-while asymmetric variability consisted of small, limb-specific modulations along multiple dimensions of the underlying symmetric pattern. Commands that modulated walking speed, originating from artificial neural activation or from the visual system, evoked modulations consistent with spontaneous behavior. Our findings suggest that Drosophila employ a low-dimensional control architecture, which provides a framework for understanding the neural circuits that regulate hexapod legged locomotion.

A flexible geometry for panoramic visual and optogenetic stimulation during behavior and physiology

BACKGROUND

To study visual processing, it is necessary to precisely control visual stimuli while recording neural and behavioral responses. It can be important to present stimuli over a broad area of the visual field, which can be technically difficult.

NEW METHOD

We present a simple geometry that can be used to display panoramic stimuli. A single digital light projector generates images that are reflected by mirrors onto flat screens that surround an animal. It can be used for behavioral and neurophysiological measurements, so virtually identical stimuli can be presented. Moreover, this geometry permits light from the projector to be used to activate optogenetic tools.

RESULTS

Using this geometry, we presented panoramic visual stimulation to Drosophila in three paradigms. We presented drifting contrast gratings while recording walking and turning speed. We used the same projector to activate optogenetic channels during visual stimulation. Finally, we used two-photon microscopy to record responses in direction-selective cells to drifting gratings.

COMPARISON WITH EXISTING METHOD(S)

Existing methods have typically required custom hardware or curved screens, while this method requires only flat back projection screens and a digital light projector. The projector generates images in real time and does not require pre-generated images. Finally, while many setups are large, this geometry occupies a 30 × 20 cm footprint with a 25 cm height.

CONCLUSIONS

This flexible geometry enables measurements of behavioral and neural responses to panoramic stimuli. This allows moderate throughput behavioral experiments with simultaneous optogenetic manipulation, with easy comparisons between behavior and neural activity using virtually identical stimuli.

Kinetics of maternally-derived serogroup A, C, Y and W-specific meningococcal immunoglobulin G in Malian women and infants

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Immunisation with MCV during pregnancy resulted in an antibody response.

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Maternal immunization with MCV conveyed protective levels of MenA IgG at birth.

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Infant antibody levels declined over the first 3 months of life.

A prospective, randomised, controlled observer-blind trial measuring the efficacy and immunogenicity of trivalent influenza vaccine (TIV) and the immunogenicity of quadrivalent meningococcal conjugate vaccine (MCV) in pregnant women and their infants up to 6 months of age was conducted in Mali. Here we reported the immunogenicity of MCV, which was used as a comparator vaccine to TIV, in this population. Third-trimester pregnant Malian women were randomized to receive TIV or MCV. Blood samples were collected from women prior to vaccination, 28 days post-vaccination, at delivery and 3 and 6 months post-delivery and from infants at birth and 3 and 6 months of age. Meningococcal-specific serogroup (Men) A, C, Y and W-specific antibodies were measured by enzyme linked immunosorbent assay in a randomly selected subset of 50 mother-infant pairs where the mother had received MCV. At birth, 94.0% (47/50) of infants had MenA specific IgG levels ≥ 2 µg/mL decreasing to 72.9% and 30.4% at 3 and 6 months of age. For MenC, 81.3% (39/48) of infants had MenC specific IgG levels ≥ 2 µg/mL at birth decreasing to 29.4% and 17.8% at 3 and 6 months of age. For MenY, 89.6% (43/48) of infants had MenY specific IgG levels ≥ 2 µg/mL at birth decreasing to 64.6% and 62.5% at 3 and 6 months of age. For MenW, 89.6% (43/48) of infants had MenW specific IgG levels ≥ 2 μg/ml at birth decreasing to 62.5% and 41.7% at 3 and 6 months of age.

Maternal immunization with MCV conveyed protective levels of IgG at birth through to 3 months of age in the majority of infants.

Drain fluid amylase as a sensitive biomarker for the early detection of anastomotic leakage in ileal pouch surgery

AIM

We studied the levels of amylase in drain fluid to investigate its utility as a biomarker of anastomotic leak in ileal pouch patients who did not have a covering loop ileostomy. The luminal contents of the small intestine are high in amylase. Ileal J pouches are formed for restoration of continuity in patients with ulcerative colitis after removal of the colon and rectum. A drain is placed alongside the ileal pouch in the pelvis.

METHOD

This study is a retrospective analysis of prospectively collected daily drain fluid amylase levels in consecutive patients undergoing restorative proctectomy and ileal J pouch anal anastomosis, without a covering loop ileostomy, between November 2016 and April 2018.

RESULTS

Thirteen patients underwent surgery without a covering loop ileostomy. Two patients suffered an anastomotic leak and were returned to theatre, one on day 5 and the other on day 6 postoperatively. The mean daily drain fluid amylase level in those who did not leak was between 25 and 46 U/l with a range of 22-139 U/l for all samples collected. In the two patients who suffered a clinical leak the drain fluid amylase level rose to 22 432 and 10 212 U/l on the day of clinical leak diagnosis. The mean rectal tube (intraluminal) amylase level was 63 097 U/l as measured on day 1 postoperatively.

CONCLUSION

In this small cohort of patients, the measurement of drain fluid amylase is a highly sensitive biomarker of clinical anastomotic leak.

Myofibroblast proliferation and heterogeneity are supported by macrophages during skin repair

During tissue repair, myofibroblasts produce extracellular matrix (ECM) molecules for tissue resilience and strength. Altered ECM deposition can lead to tissue dysfunction and disease. Identification of distinct myofibroblast subsets is necessary to develop treatments for these disorders. We analyzed profibrotic cells during mouse skin wound healing, fibrosis, and aging and identified distinct subpopulations of myofibroblasts, including adipocyte precursors (APs). Multiple mouse models and transplantation assays demonstrate that proliferation of APs but not other myofibroblasts is activated by CD301b-expressing macrophages through insulin-like growth factor 1 and platelet-derived growth factor C. With age, wound bed APs and differential gene expression between myofibroblast subsets are reduced. Our findings identify multiple fibrotic cell populations and suggest that the environment dictates functional myofibroblast heterogeneity, which is driven by fibroblast-immune interactions after wounding.

The Neuronal Basis of an Illusory Motion Percept Is Explained by Decorrelation of Parallel Motion Pathways

Both vertebrates and invertebrates perceive illusory motion, known as "reverse-phi," in visual stimuli that contain sequential luminance increments and decrements. However, increment (ON) and decrement (OFF) signals are initially processed by separate visual neurons, and parallel elementary motion detectors downstream respond selectively to the motion of light or dark edges, often termed ON- and OFF-edges. It remains unknown how and where ON and OFF signals combine to generate reverse-phi motion signals. Here, we show that each of Drosophila's elementary motion detectors encodes motion by combining both ON and OFF signals. Their pattern of responses reflects combinations of increments and decrements that co-occur in natural motion, serving to decorrelate their outputs. These results suggest that the general principle of signal decorrelation drives the functional specialization of parallel motion detection channels, including their selectivity for moving light or dark edges.

Visual Control of Walking Speed in Drosophila

An animal's self-motion generates optic flow across its retina, and it can use this visual signal to regulate its orientation and speed through the world. While orientation control has been studied extensively in Drosophila and other insects, much less is known about the visual cues and circuits that regulate translational speed. Here, we show that flies regulate walking speed with an algorithm that is tuned to the speed of visual motion, causing them to slow when visual objects are nearby. This regulation does not depend strongly on the spatial structure or the direction of visual stimuli, making it algorithmically distinct from the classic computation that controls orientation. Despite the different algorithms, the visual circuits that regulate walking speed overlap with those that regulate orientation. Taken together, our findings suggest that walking speed is controlled by a hierarchical computation that combines multiple motion detectors with distinct tunings. VIDEO ABSTRACT.

Drosophila Sidekick is required in developing photoreceptors to enable visual motion detection

The assembly of functional neuronal circuits requires growth cones to extend in defined directions and recognize the correct synaptic partners. Homophilic adhesion between vertebrate Sidekick proteins promotes synapse formation between retinal neurons involved in visual motion detection. We show here that Drosophila Sidekick accumulates in specific synaptic layers of the developing motion detection circuit and is necessary for normal optomotor behavior. Sidekick is required in photoreceptors, but not in their target lamina neurons, to promote the alignment of lamina neurons into columns and subsequent sorting of photoreceptor axons into synaptic modules based on their precise spatial orientation. Sidekick is also localized to the dendrites of the direction-selective T4 and T5 cells, and is expressed in some of their presynaptic partners. In contrast to its vertebrate homologs, Sidekick is not essential for T4 and T5 to direct their dendrites to the appropriate layers or to receive synaptic contacts. These results illustrate a conserved requirement for Sidekick proteins in establishing visual motion detection circuits that is achieved through distinct cellular mechanisms in Drosophila and vertebrates.

Parallel Computations in Insect and Mammalian Visual Motion Processing

Sensory systems use receptors to extract information from the environment and neural circuits to perform subsequent computations. These computations may be described as algorithms composed of sequential mathematical operations. Comparing these operations across taxa reveals how different neural circuits have evolved to solve the same problem, even when using different mechanisms to implement the underlying math. In this review, we compare how insect and mammalian neural circuits have solved the problem of motion estimation, focusing on the fruit fly Drosophila and the mouse retina. Although the two systems implement computations with grossly different anatomy and molecular mechanisms, the underlying circuits transform light into motion signals with strikingly similar processing steps. These similarities run from photoreceptor gain control and spatiotemporal tuning to ON and OFF pathway structures, motion detection, and computed motion signals. The parallels between the two systems suggest that a limited set of algorithms for estimating motion satisfies both the needs of sighted creatures and the constraints imposed on them by metabolism, anatomy, and the structure and regularities of the visual world.

Direct Measurement of Correlation Responses in Drosophila Elementary Motion Detectors Reveals Fast Timescale Tuning

Animals estimate visual motion by integrating light intensity information over time and space. The integration requires nonlinear processing, which makes motion estimation circuitry sensitive to specific spatiotemporal correlations that signify visual motion. Classical models of motion estimation weight these correlations to produce direction-selective signals. However, the correlational algorithms they describe have not been directly measured in elementary motion-detecting neurons (EMDs). Here, we employed stimuli to directly measure responses to pairwise correlations in Drosophila's EMD neurons, T4 and T5. Activity in these neurons was required for behavioral responses to pairwise correlations and was predictive of those responses. The pattern of neural responses in the EMDs was inconsistent with one classical model of motion detection, and the timescale and selectivity of correlation responses constrained the temporal filtering properties in potential models. These results reveal how neural responses to pairwise correlations drive visual behavior in this canonical motion-detecting circuit.

Olfactory receptor neurons use gain control and complementary kinetics to encode intermittent odorant stimuli

Insects find food and mates by navigating odorant plumes that can be highly intermittent, with intensities and durations that vary rapidly over orders of magnitude. Much is known about olfactory responses to pulses and steps, but it remains unclear how olfactory receptor neurons (ORNs) detect the intensity and timing of natural stimuli, where the absence of scale in the signal makes detection a formidable olfactory task. By stimulating Drosophila ORNs in vivo with naturalistic and Gaussian stimuli, we show that ORNs adapt to stimulus mean and variance, and that adaptation and saturation contribute to naturalistic sensing. Mean-dependent gain control followed the Weber-Fechner relation and occurred primarily at odor transduction, while variance-dependent gain control occurred at both transduction and spiking. Transduction and spike generation possessed complementary kinetic properties, that together preserved the timing of odorant encounters in ORN spiking, regardless of intensity. Such scale-invariance could be critical during odor plume navigation.

Trochleoplasty with a flexible osteochondral flap: results from an 11-year series of 214 cases

AIMS

The Bereiter trochleoplasty has been used in our unit for 12 years to manage recurrent patellar instability in patients with severe trochlea dysplasia. The aim of this study was to document the outcome of a large consecutive cohort of patients who have undergone this operation.

PATIENTS AND METHODS

Between June 2002 and August 2013, 214 consecutive trochleoplasties were carried out in 185 patients. There were 133 women and 52 men with a mean age of 21.3 years (14 to 38). All patients were offered yearly clinical and radiological follow-up. They completed the following patient reported outcome scores (PROMs): International Knee Documentation Committee subjective scale, the Kujala score, the Western Ontario and McMaster Universities Arthritis Index score and the short-form (SF)-12.

RESULTS

Outcomes were available for 199 trochleoplasties in 173 patients giving a 93% follow-up rate at a mean of 4.43 years (1 to 12). There were no infections or deep vein thromboses. In total, 16 patients reported further patella dislocation, giving an 8.3% rate of recurrence. There were 27 re-operations, giving a rate of re-operation of 14%. Overall, 88% were satisfied with the operation and 90% felt that their symptoms had been improved.

CONCLUSION

All PROMs improved significantly post-operatively except for the mental component score of the SF-12. Trochleoplasty performed using a flexible osteochondral flap is an effective treatment for recurrent patellar instability in patients with severe trochlea dysplasia and gives good results in the medium term. Cite this article: Bone Joint J 2017;99-B:344-50.

Graphics Processing Unit-Accelerated Code for Computing Second-Order Wiener Kernels and Spike-Triggered Covariance

Sensory neuroscience seeks to understand and predict how sensory neurons respond to stimuli. Nonlinear components of neural responses are frequently characterized by the second-order Wiener kernel and the closely-related spike-triggered covariance (STC). Recent advances in data acquisition have made it increasingly common and computationally intensive to compute second-order Wiener kernels/STC matrices. In order to speed up this sort of analysis, we developed a graphics processing unit (GPU)-accelerated module that computes the second-order Wiener kernel of a system's response to a stimulus. The generated kernel can be easily transformed for use in standard STC analyses. Our code speeds up such analyses by factors of over 100 relative to current methods that utilize central processing units (CPUs). It works on any modern GPU and may be integrated into many data analysis workflows. This module accelerates data analysis so that more time can be spent exploring parameter space and interpreting data.

Nonlinear circuits for naturalistic visual motion estimation

Many animals use visual signals to estimate motion. Canonical models suppose that animals estimate motion by cross-correlating pairs of spatiotemporally separated visual signals, but recent experiments indicate that humans and flies perceive motion from higher-order correlations that signify motion in natural environments. Here we show how biologically plausible processing motifs in neural circuits could be tuned to extract this information. We emphasize how known aspects of Drosophila's visual circuitry could embody this tuning and predict fly behavior. We find that segregating motion signals into ON/OFF channels can enhance estimation accuracy by accounting for natural light/dark asymmetries. Furthermore, a diversity of inputs to motion detecting neurons can provide access to more complex higher-order correlations. Collectively, these results illustrate how non-canonical computations improve motion estimation with naturalistic inputs. This argues that the complexity of the fly's motion computations, implemented in its elaborate circuits, represents a valuable feature of its visual motion estimator.

DOI:http://dx.doi.org/10.7554/eLife.09123.001

Many animals have evolved the ability to estimate the speed and direction of visual motion. They use these estimates to judge their own motion, so that they can navigate through an environment, and to judge how other animals are moving, which allows them to avoid predators or detect prey.

In the 1950s, a physicist and a biologist used measurements of beetle behavior in response to visual stimuli to develop a model for how the brain estimates motion. The model became known as the Hassenstein-Reichardt correlator (HRC). The HRC and related models accurately predict the behavioral and neural responses of insects and mammals to many types of motion stimuli.

However, there are visual stimuli that generate motion percepts in fruit flies (and humans) that cannot be accounted for by the HRC. Are these differences between real brains and the HRC simply imperfections in visual circuits, whose neurons cannot perform idealized mathematical operations, or are these deviations intentional, somehow improving motion estimates? In other words: are the observed deviations a bug or a feature of visual circuits?

To address this question, Fitzgerald and Clark evaluated how different models of motion detection performed when presented with natural scenes. Natural scenes are fundamentally different from most stimuli used in lab, since they contain a rich set of regularities that are not present in simple stimuli. Fitzgerald and Clark compared the ability of the HRC, along with new, more general models, to estimate the speed and direction at which images moved across a screen. This revealed that many models could out-perform the HRC by taking advantage of regularities in natural scenes. Those models that were tuned to perform well with natural scenes could also predict the paradoxical motion percepts that were not predicted by the HRC. This suggests that visual circuits may have evolved to perform well with natural inputs, and the paradoxical motion percepts represent a feature of the real circuit, rather than a bug.

Models that performed well with natural inputs treated light and dark visual information differently. This different treatment of light and dark is a property of most visual systems, but not of the HRC or related models. In the future, these models of motion processing may help us understand how biological details of the fruit fly's visual circuits help it to estimate motion.

DOI:http://dx.doi.org/10.7554/eLife.09123.002

Rods in daylight act as relay cells for cone-driven horizontal cell-mediated surround inhibition

Vertebrate vision relies on two types of photoreceptors, rods and cones, which signal increments in light intensity with graded hyperpolarizations. Rods operate in the lower range of light intensities while cones operate at brighter intensities. The receptive fields of both photoreceptors exhibit antagonistic center-surround organization. Here we show that at bright light levels, mouse rods act as relay cells for cone-driven horizontal cell-mediated surround inhibition. In response to large, bright stimuli that activate their surrounds, rods depolarize. Rod depolarization increases with stimulus size, and its action spectrum matches that of cones. Rod responses at high light levels are abolished in mice with nonfunctional cones and when horizontal cells are reversibly inactivated. Rod depolarization is conveyed to the inner retina via postsynaptic circuit elements, namely the rod bipolar cells. Our results show that the retinal circuitry repurposes rods, when they are not directly sensing light, to relay cone-driven surround inhibition.

Walking Drosophila align with the e-vector of linearly polarized light through directed modulation of angular acceleration

Understanding the mechanisms that link sensory stimuli to animal behavior is a central challenge in neuroscience. The quantitative description of behavioral responses to defined stimuli has led to a rich understanding of different behavioral strategies in many species. One important navigational cue perceived by many vertebrates and insects is the e-vector orientation of linearly polarized light. Drosophila manifests an innate orientation response to this cue ('polarotaxis'), aligning its body axis with the e-vector field. We have established a population-based behavioral paradigm for the genetic dissection of neural circuits guiding polarotaxis to both celestial as well as reflected polarized stimuli. However, the behavioral mechanisms by which flies align with a linearly polarized stimulus remain unknown. Here, we present a detailed quantitative description of Drosophila polarotaxis, systematically measuring behavioral parameters that are modulated by the stimulus. We show that angular acceleration is modulated during alignment, and this single parameter may be sufficient for alignment. Furthermore, using monocular deprivation, we show that each eye is necessary for modulating turns in the ipsilateral direction. This analysis lays the foundation for understanding how neural circuits guide these important visual behaviors.

Dynamical adaptation in photoreceptors

Adaptation is at the heart of sensation and nowhere is it more salient than in early visual processing. Light adaptation in photoreceptors is doubly dynamical: it depends upon the temporal structure of the input and it affects the temporal structure of the response. We introduce a non-linear dynamical adaptation model of photoreceptors. It is simple enough that it can be solved exactly and simulated with ease; analytical and numerical approaches combined provide both intuition on the behavior of dynamical adaptation and quantitative results to be compared with data. Yet the model is rich enough to capture intricate phenomenology. First, we show that it reproduces the known phenomenology of light response and short-term adaptation. Second, we present new recordings and demonstrate that the model reproduces cone response with great precision. Third, we derive a number of predictions on the response of photoreceptors to sophisticated stimuli such as periodic inputs, various forms of flickering inputs, and natural inputs. In particular, we demonstrate that photoreceptors undergo rapid adaptation of response gain and time scale, over ∼ 300[Formula: see text] ms-i. e., over the time scale of the response itself-and we confirm this prediction with data. For natural inputs, this fast adaptation can modulate the response gain more than tenfold and is hence physiologically relevant.

Modular use of peripheral input channels tunes motion-detecting circuitry

In the visual system, peripheral processing circuits are often tuned to specific stimulus features. How this selectivity arises and how these circuits are organized to inform specific visual behaviors is incompletely understood. Using forward genetics and quantitative behavioral studies, we uncover an input channel to motion detecting circuitry in Drosophila. The second-order neuron L3 acts combinatorially with two previously known inputs, L1 and L2, to inform circuits specialized to detect moving light and dark edges. In vivo calcium imaging of L3, combined with neuronal silencing experiments, suggests a neural mechanism to achieve selectivity for moving dark edges. We further demonstrate that different innate behaviors, turning and forward movement, can be independently modulated by visual motion. These two behaviors make use of different combinations of input channels. Such modular use of input channels to achieve feature extraction and behavioral specialization likely represents a general principle in sensory systems.

GABAergic lateral interactions tune the early stages of visual processing in Drosophila

Early stages of visual processing must capture complex, dynamic inputs. While peripheral neurons often implement efficient encoding by exploiting natural stimulus statistics, downstream neurons are specialized to extract behaviorally relevant features. How do these specializations arise? We use two-photon imaging in Drosophila to characterize a first-order interneuron, L2, that provides input to a pathway specialized for detecting moving dark edges. GABAergic interactions, mediated in part presynaptically, create an antagonistic and anisotropic center-surround receptive field. This receptive field is spatiotemporally coupled, applying differential temporal processing to large and small dark objects, achieving significant specialization. GABAergic circuits also mediate OFF responses and balance these with responses to ON stimuli. Remarkably, the functional properties of L2 are strikingly similar to those of bipolar cells, yet emerge through different molecular and circuit mechanisms. Thus, evolution appears to have converged on a common strategy for processing visual information at the first synapse.

Mapping and cracking sensorimotor circuits in genetic model organisms

One central goal of systems neuroscience is to understand how neural circuits implement the computations that link sensory inputs to behavior. Work combining electrophysiological and imaging-based approaches to measure neural activity with pharmacological and electrophysiological manipulations has provided fundamental insights. More recently, genetic approaches have been used to monitor and manipulate neural activity, opening up new experimental opportunities and challenges. Here, we discuss issues associated with applying genetic approaches to circuit dissection in sensorimotor transformations, outlining important considerations for experimental design and considering how modeling can complement experimental approaches.

Surgical outcomes in steroid refractory acute severe ulcerative colitis: the impact of rescue therapy

AIM

The advent of rescue medical therapy (cyclosporin or infliximab) and laparoscopic surgery has shifted the paradigm in managing steroid refractory acute severe ulcerative colitis (ASUC). We investigated prospectively the impact of rescue therapy on timing and postoperative complications of urgent colectomy and subsequent restorative surgery for steroid refractory ASUC.

METHOD

All consecutive presentations of steroid refractory ASUC at the Royal Brisbane Hospital (1996-2009) were entered in the study. Data collated included demographics, clinical and laboratory parameters on admission, medical therapy and operative and postoperative details. Steroid refractory ASUC patients undergoing immediate colectomy were compared with those failing rescue therapy and requiring same admission colectomy.

RESULTS

Of 108 steroid refractory ASUC presentations, 19 (18%) received intravenous steroids only and proceeded directly to colectomy. Rescue medical therapy was instituted in 89 (82%) patients with 30 (34%) failing to respond and proceeding to colectomy. There was no significant difference in the median time from admission to colectomy for rescue therapy compared with steroid-only cases (12 vs 10 days, P = 0.70) or 30-day complication rates (27%vs 47%, P = 0.22). The interval from colectomy to a subsequent restorative procedure was significantly longer for patients who failed rescue therapy (12 vs 5 months, P = 0.02). Furthermore 30-day complications following pouch surgery were significantly higher in patients who failed rescue therapy (32%vs 0%, P = 0.01).

CONCLUSION

Rescue therapy in steroid refractory ASUC is not related to delay in urgent colectomy or increased post-colectomy complications.

Regeneration of canopy trees in tropical wet forests

The most diverse tree communities on earth, the tropical wet forests, to a large degree remain ecological enigmas. What accounts for the coexistence of 100 or more tree species per hectare, compared to the 15 or fewer found in most temperate forests? What are the lifespans of tropical forest trees? What factors control their populations through time and space? Do the different species have highly individual regeneration patterns, or are many in fact ecological equivalents? Although we are far from having satisfactory answers to these questions, recent studies of regeneration processes are leading toward new interpretations of these complex communities.

Comparison of the QIAGEN artus HIV-1 QS-RGQ test with the Roche COBAS AmpliPrep/COBAS TaqMan HIV-1 test v2.0

BACKGROUND

Regular HIV-1 viral load monitoring is standard of care in the developed world for patients infected with HIV-1.

OBJECTIVES

Here we report a comparative evaluation of the established Roche COBAS AmpliPrep/COBAS TaqMan HIV-1 v2.0 test (Roche Diagnostics Ltd, Burgess Hill, UK) and the new artus HIV-1 QS-RGQ test (QIAGEN Ltd, Crawley, UK).

STUDY DESIGN

169 clinical EDTA-plasma samples were tested, all of known HIV-1 subtype.

RESULTS

The mean overall log(10)c/ml difference was 0.10 (QIAGEN - Roche).

CONCLUSION

The artus HIV-1 QS-RGQ test compared well with the Roche TaqMan HIV-1 v2.0 test, and Bland-Altman analysis showed good agreement between the two systems across a wide range of subtypes.

Dopamine signaling is essential for precise rates of locomotion by C. elegans

Dopamine is an important neuromodulator in both vertebrates and invertebrates. We have found that reduced dopamine signaling can cause a distinct abnormality in the behavior of the nematode C. elegans, which has only eight dopaminergic neurons. Using an automated particle-tracking system for the analysis of C. elegans locomotion, we observed that individual wild-type animals made small adjustments to their speed to maintain constant rates of locomotion. By contrast, individual mutant animals defective in the synthesis of dopamine made larger adjustments to their speeds, resulting in large fluctuations in their rates of locomotion. Mutants defective in dopamine signaling also frequently exhibited both abnormally high and abnormally low average speeds. The ability to make small adjustments to speed was restored to these mutants by treatment with dopamine. These behaviors depended on the D2-like dopamine receptor DOP-3 and the G-protein subunit GOA-1. We suggest that C. elegans and other animals, including humans, might share mechanisms by which dopamine restricts motor activity levels and coordinates movement.

The relationship between milk production and farm-gate nitrogen surplus for the Waikato region, New Zealand

As the scope and scale of New Zealand (NZ) dairy farming increases, farmers and the industry are being challenged by Government and the New Zealand public to address growing environmental concerns. Dairying has come under increasing scrutiny from local authorities tasked with sustainable resource management. Despite recent efforts of farmers and industry to improve resource use efficiency, there is increasing likelihood of further regulatory constraints on water use and nutrient management. This study uses available data on farm-gate nitrogen (N) surpluses and milk production from the Waikato, New Zealand's largest dairying region, together with a farm scale modeling exercise, to provide a perspective on the current situation compared to dairy farms in Europe. It also aims to provide relevant guidelines for N surpluses and efficiencies under NZ conditions. Waikato dairy farms compare favorably with farms in Europe in terms of N use efficiency expressed as L milk/kg farm-gate N surplus. Achievable and realistic good practice objectives for Waikato dairy farmers could be 15,000 L milk/ha (1200 kg milk fat plus protein/ha) with a farm-gate N surplus of 100 kg/ha giving an eco-efficiency (L milk/kg N surplus) of 150, and long-term average nitrate leaching losses of approximately 25-30 kg/ha/yr. This can be achieved by increasing the N conversion efficiency through lower replacement rates (16 versus 22%), lower stocked (< 3 cows/ha) high genetic merit cows (30 L milk/day at peak) milked for longer (277 versus 240 days), feeding effluent-irrigated, home-grown, low-protein supplements to cows on high-protein, grass-clover pastures to dilute N concentration in the diet, removing some of the urinary N from the paddocks during critical times by standing cows on a loafing pad for part of the day, and through lower N fertilizer rates (50-70 kg/ha/yr compared to the norm of 170-200 kg/ha/yr) and using a nitrification inhibitor and gibberellins to boost pasture growth and the former to reduce N leaching.

Genetic dissection reveals two separate retinal substrates for polarization vision in Drosophila

BACKGROUND

Linearly polarized light originates from atmospheric scattering or surface reflections and is perceived by insects, spiders, cephalopods, crustaceans, and some vertebrates. Thus, the neural basis underlying how this fundamental quality of light is detected is of broad interest. Morphologically unique, polarization-sensitive ommatidia exist in the dorsal periphery of many insect retinas, forming the dorsal rim area (DRA). However, much less is known about the retinal substrates of behavioral responses to polarized reflections.

SUMMARY

Drosophila exhibits polarotactic behavior, spontaneously aligning with the e-vector of linearly polarized light, when stimuli are presented either dorsally or ventrally. By combining behavioral experiments with genetic dissection and ultrastructural analyses, we show that distinct photoreceptors mediate the two behaviors: inner photoreceptors R7+R8 of DRA ommatidia are necessary and sufficient for dorsal polarotaxis, whereas ventral responses are mediated by combinations of outer and inner photoreceptors, both of which manifest previously unknown features that render them polarization sensitive.

CONCLUSIONS

Drosophila uses separate retinal pathways for the detection of linearly polarized light emanating from the sky or from shiny surfaces. This work establishes a behavioral paradigm that will enable genetic dissection of the circuits underlying polarization vision.