Sector search strategies for odor trail tracking.
Ontology highlight
ABSTRACT:
SUBMITTER: Reddy G
PROVIDER: S-EPMC8740577 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundRegarding the leprosy transmission through the upper airways, overcrowded locations such as prisons can become a risk to get sick. Like the leprosy hidden endemic demonstrated in male prison population, being interesting to assess the leprosy scene also among confined women.MethodsA prospective descriptive study conducted at Female Penitentiary, Brazil. Leprosy Suspicion Questionnaire (LSQ) were applied to the participants, and submitted to specialized dermatoneurological exam, peripheral nerve ultrasonography, and anti-PGL-I serology.Findings404 female inmates were evaluated, 14 new cases were diagnosed (LG-leprosy group), a new case detection rate (NCDR) of 3.4%, 13 multibacillary, while another 390 constituted the Non-Leprosy group (NLG). Leprosy cases were followed up during multidrug therapy with clinical improvement. The confinement time median was 31 months in LG, similar to NLG, less than the time of leprosy incubation. Regarding LSQ, the neurological symptoms reached the highest x2 values as Q1-numbness (5.6), Q3-anesthetizes areas in the skin (7.5), Q5-Stinging sensation (5.8), and Q7-pain in the nerves (34.7), while Q4-spots on the skin was 4.94. When more than one question were marked in the LSQ means a 12.8-fold higher to have the disease than a subject who marked only one or none. The high 34% rate of anti-PGL-I seropositivity in the penitentiary, higher levels in LG than NLG. Three additional leprosy cases each were diagnosed on the second (n = 66) and third (n = 14) reevaluations 18 and 36 months after the initial one. Semmes-Weinstein monofilaments demonstrated lower limbs (32.2%) more affected than the upper limbs (25%) with improvement during the follow-up.InterpretationThe NCDR in this population showed an hidden endemic of leprosy as well as the efficacy of a search action on the part of a specialized team with the aid of the LSQ and anti-PGL-I serology as an auxiliary tracking tools.
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Project description:Navigating an odor landscape is a critical behavior for the survival of many species, including mice. An ethologically relevant mouse behavior is locating food using information about odor concentration. To approximate this behavior, we used an open field odor-based spot-finding task indoors with little wind, examining navigation strategies as mice search for and approach an odor source. After mice were trained to navigate to odor sources paired with food reward, we observed behavioral changes consistent with localization 10-45 cm away from the source. These behaviors included orientation toward the source, decreased velocity, and increased exploration time. We also found that the amplitude of 'casting,' which we define as lateral back and forth movement of the nose, increased with proximity to the source. Based on these observations, we created a concentration-sensitive agent-based model to simulate mouse behavior. This model provided evidence for a binaral-sniffing strategy (inter-nostril comparison of concentration in a single sniff) and a serial-sniffing strategy (sampling concentration, moving in space, and then sampling again). Serial-sniffing may be accomplished at farther distances by moving the body and at closer distances by moving the head (casting). Together, these results elucidate components of behavioral strategies for odor-based navigation.
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Project description:Casting behavior (zigzagging across an odor stream) is common in air/liquid-borne odor tracking in open fields; however, terrestrial odor localization often involves path selection in a familiar environment. To study this, we trained rats to run toward an odor source in a multi-choice olfactory arena with near-laminar airflow. We find that rather than casting, rats run directly toward an odor port, and if this is incorrect, they serially sample other sources. This behavior is consistent and accurate in the presence of perturbations, such as novel odors, background odor, unilateral nostril stitching, and turbulence. We developed a model that predicts that this run-and-scan tracking of air-borne odors is faster than casting, provided there are a small number of targets at known locations. Thus, the combination of best-guess target selection with fallback serial sampling provides a rapid and robust strategy for finding odor sources in familiar surroundings.
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Project description:Natural decision-making often involves extended decision sequences in response to variable stimuli with complex structure. As an example, many animals follow odor plumes to locate food sources or mates, but turbulence breaks up the advected odor signal into intermittent filaments and puffs. This scenario provides an opportunity to ask how animals use sparse, instantaneous, and stochastic signal encounters to generate goal-oriented behavioral sequences. Here we examined the trajectories of flying fruit flies (Drosophila melanogaster) and mosquitoes (Aedes aegypti) navigating in controlled plumes of attractive odorants. While it is known that mean odor-triggered flight responses are dominated by upwind turns, individual responses are highly variable. We asked whether deviations from mean responses depended on specific features of odor encounters, and found that odor-triggered turns were slightly but significantly modulated by two features of odor encounters. First, encounters with higher concentrations triggered stronger upwind turns. Second, encounters occurring later in a sequence triggered weaker upwind turns. To contextualize the latter history dependence theoretically, we examined trajectories simulated from three normative tracking strategies. We found that neither a purely reactive strategy nor a strategy in which the tracker learned the plume centerline over time captured the observed history dependence. In contrast, "infotaxis", in which flight decisions maximized expected information gain about source location, exhibited a history dependence aligned in sign with the data, though much larger in magnitude. These findings suggest that while true plume tracking is dominated by a reactive odor response it might also involve a history-dependent modulation of responses consistent with the accumulation of information about a source over multi-encounter timescales. This suggests that short-term memory processes modulating decision sequences may play a role in natural plume tracking.
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Project description:Internal physiological states influence behavioral decisions. We have investigated the underlying cellular and molecular mechanisms at the first olfactory synapse for starvation modulation of food-search behavior in Drosophila. We found that a local signal by short neuropeptide F (sNPF) and a global metabolic cue by insulin are integrated at specific odorant receptor neurons (ORNs) to modulate olfactory sensitivity. Results from two-photon calcium imaging show that starvation increases presynaptic activity via intraglomerular sNPF signaling. Expression of sNPF and its receptor (sNPFR1) in Or42b neurons is necessary for starvation-induced food-search behavior. Presynaptic facilitation in Or42b neurons is sufficient to mimic starvation-like behavior in fed flies. Furthermore, starvation elevates the transcription level of sNPFR1 but not that of sNPF, and insulin signaling suppresses sNPFR1 expression. Thus, starvation increases expression of sNPFR1 to change the odor map, resulting in more robust food-search behavior.
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Project description:Previous research has demonstrated that various properties of infectious diseases can be inferred from online search behaviour. In this work we use time series of online search query frequencies to gain insights about the prevalence of COVID-19 in multiple countries. We first develop unsupervised modelling techniques based on associated symptom categories identified by the United Kingdom's National Health Service and Public Health England. We then attempt to minimise an expected bias in these signals caused by public interest-as opposed to infections-using the proportion of news media coverage devoted to COVID-19 as a proxy indicator. Our analysis indicates that models based on online searches precede the reported confirmed cases and deaths by 16.7 (10.2-23.2) and 22.1 (17.4-26.9) days, respectively. We also investigate transfer learning techniques for mapping supervised models from countries where the spread of the disease has progressed extensively to countries that are in earlier phases of their respective epidemic curves. Furthermore, we compare time series of online search activity against confirmed COVID-19 cases or deaths jointly across multiple countries, uncovering interesting querying patterns, including the finding that rarer symptoms are better predictors than common ones. Finally, we show that web searches improve the short-term forecasting accuracy of autoregressive models for COVID-19 deaths. Our work provides evidence that online search data can be used to develop complementary public health surveillance methods to help inform the COVID-19 response in conjunction with more established approaches.
| S-EPMC7870878 | biostudies-literature
Project description:Localization of odors is essential to animal survival, and thus animals are adept at odor navigation. In natural conditions animals encounter odor sources in which odor is carried by air flow varying in complexity. We sought to identify potential minimalist strategies that can effectively be used for odor-based navigation and asses their performance in an increasingly chaotic environment. To do so, we compared mouse, in silico model, and Arduino-based robot odor-localization behavior in a standardized odor landscape. Mouse performance remains robust in the presence of increased complexity, showing a shift in strategy towards faster movement with increased environmental complexity. Implementing simple binaral and temporal models of tropotaxis and klinotaxis, an in silico model and Arduino robot, in the same environment as the mice, are equally successful in locating the odor source within a plume of low complexity. However, performance of these algorithms significantly drops when the chaotic nature of the plume is increased. Additionally, both algorithm-driven systems show more successful performance when using a strictly binaral model at a larger sensor separation distance and more successful performance when using a temporal and binaral model when using a smaller sensor separation distance. This suggests that with an increasingly chaotic odor environment, mice rely on complex strategies that allow for robust odor localization that cannot be resolved by minimal algorithms that display robust performance at low levels of complexity. Thus, highlighting that an animal's ability to modulate behavior with environmental complexity is beneficial for odor localization.
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Project description:BackgroundTurbulent fluid landscapes impose temporal patterning upon chemical signals, and the dynamical neuronal responses to patterned input vary across the olfactory receptor repertoire in flies, moths, and locusts. Sensory transformations exhibit low pass filtering that ultimately results in perceptual fusion of temporally transient sensory signals. For example, humans perceive a sufficiently fast flickering light as continuous, but the frequency threshold at which this fusion occurs varies with wavelength. Although the summed frequency sensitivity of the fly antenna has been examined to a considerable extent, it is unknown how intermittent odor signals are integrated to influence plume tracking behavior independent of wind cues, and whether temporal fusion for behavioral tracking might vary according to the odor encountered.ResultsHere we have adopted a virtual reality flight simulator to study the dynamics of plume tracking under different experimental conditions. Flies tethered in a magnetic field actively track continuous (non-intermittent) plumes of vinegar, banana, or ethyl butyrate with equal precision. However, pulsing these plumes at varying frequency reveals that the threshold rate, above which flies track the plume as if it were continuous, is unique for each odorant tested. Thus, the capability of a fly to navigate an intermittent plume depends on the particular odorant being tracked during flight. Finally, we measured antennal field potential responses to an intermittent plume, found that receptor dynamics track the temporal pattern of the odor stimulus and therefore do not limit the observed behavioral temporal fusion limits.ConclusionsThis study explores the flies' ability to track odor plumes that are temporally intermittent. We were surprised to find that the perceptual critical fusion limit, determined behaviorally, is strongly dependent on odor identity. Antennal field potential recordings indicate that peripheral processing of temporal cues faithfully follow rapid odor transients above the rates that can be resolved behaviorally. These results indicate that (1) higher order circuits create a perceptually continuous signal from an intermittent sensory one, and that (2) this transformation varies with odorant rather than being constrained by sensory-motor integration, thus (3) offering an entry point for examining the mechanisms of rapid olfactory decision making in an ecological context.
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