Dynamical modeling of collective behavior from pigeon flight data: flock cohesion and dispersion

Several models of flocking have been promoted based on simulations with qualitatively naturalistic behavior. In this paper we provide the first direct application of computational modeling methods to infer flocking behavior from experimental field data. We show that this approach is able to infer general rules for interaction, or lack of interaction, among members of a flock or, more generally, any community. Using experimental field measurements of homing pigeons in flight we demonstrate the existence of a basic distance dependent attraction/repulsion relationship and show that this rule is sufficient to explain collective behavior observed in nature. Positional data of individuals over time are used as input data to a computational algorithm capable of building complex nonlinear functions that can represent the system behavior. Topological nearest neighbor interactions are considered to characterize the components within this model. The efficacy of this method is demonstrated with simulated noisy data generated from the classical (two dimensional) Vicsek model. When applied to experimental data from homing pigeon flights we show that the more complex three dimensional models are capable of predicting and simulating trajectories, as well as exhibiting realistic collective dynamics. The simulations of the reconstructed models are used to extract properties of the collective behavior in pigeons, and how it is affected by changing the initial conditions of the system. Our results demonstrate that this approach may be applied to construct models capable of simulating trajectories and collective dynamics using experimental field measurements of herd movement. From these models, the behavior of the individual agents (animals) may be inferred

Stereodifferentiation in the intramolecular singlet excited state quenching of hydroxybiphenyl-tryptophan dyads

The photochemical processes occurring in diastereomeric dyads (S, S)-1 and (S, R)-1, prepared by conjugation of (S)-2-(2-hydroxy-1,1'-biphenyl-4-yl) propanoic acid ((S)-BPOH) with (S)- and (R)-Trp, have been investigated. In acetonitrile, the fluorescence spectra of (S, S)-1 and (S, R)-1 were coincident in shape and position with that of (S)-BPOH, although they revealed a markedly stereoselective quenching. Since singlet energy transfer from BPOH to Trp is forbidden (5 kcal mol(-1) uphill), the quenching was attributed to thermodynamically favoured (according to Rehm-Weller) electron transfer or exciplex formation. Upon addition of 20% water, the fluorescence quantum yield of (S)-BPOH decreased, while only minor changes were observed for the dyads. This can be explained by an enhancement of the excited state acidity of (S)-BPOH, associated with bridging of the carboxy and hydroxy groups by water, in agreement with the presence of water molecules in the X-ray structure of (S)-BPOH. When the carboxy group was not available for coordination with water, as in the methyl ester (S)-BPOHMe or in the dyads, this effect was prevented; accordingly, the fluorescence quantum yields did not depend on the presence or absence of water. The fluorescence lifetimes in dry acetonitrile were 1.67, 0.95 and 0.46 ns for (S)-BPOH, (S, S)-1 and (S, R)-1, respectively, indicating that the observed quenching is indeed dynamic. In line with the steady-state and time-resolved observations, molecular modelling pointed to a more favourable geometric arrangement of the two interacting chromophores in (S, R)-1. Interestingly, this dyad exhibited a folded conformation in the solid state.Financial support from the Spanish Government (CTQ2010-14882, BES-2008-003314, JCI-2011-09926, PR2011-0581), from the Generalitat Valenciana (Prometeo 2008/090) and from the Universitat Politecnica de Valencia (PAID 05-11, 2766) is gratefully acknowledged.Bonancía Roca, P.; Vayá Pérez, I.; Markovitsi, D.; Gustavsson, T.; Jiménez Molero, MC.; Miranda Alonso, MÁ. (2013). Stereodifferentiation in the intramolecular singlet excited state quenching of hydroxybiphenyl-tryptophan dyads. Organic and Biomolecular Chemistry. 11(12):1958-1963. https://doi.org/10.1039/c3ob27278hS195819631112Jiménez, M. C., Pischel, U., & Miranda, M. A. (2007). Photoinduced processes in naproxen-based chiral dyads. Journal of Photochemistry and Photobiology C: Photochemistry Reviews, 8(3), 128-142. doi:10.1016/j.jphotochemrev.2007.10.001Abad, S., Pischel, U., & Miranda, M. A. (2005). Wavelength-Dependent Stereodifferentiation in the Fluorescence Quenching of Asymmetric Naphthalene-Based Dyads by Amines. The Journal of Physical Chemistry A, 109(12), 2711-2717. doi:10.1021/jp047996aAbad, S., Vayá, I., Jiménez, M. C., Pischel, U., & Miranda, M. A. (2006). Diastereodifferentiation of Novel Naphthalene Dyads by Fluorescence Quenching and Excimer Formation. ChemPhysChem, 7(10), 2175-2183. doi:10.1002/cphc.200600337Bonancía, P., Vayá, I., Climent, M. J., Gustavsson, T., Markovitsi, D., Jiménez, M. C., & Miranda, M. A. (2012). Excited-State Interactions in Diastereomeric Flurbiprofen–Thymine Dyads. The Journal of Physical Chemistry A, 116(35), 8807-8814. doi:10.1021/jp3063838Paris, C., Encinas, S., Belmadoui, N., Climent, M. J., & Miranda, M. A. (2008). Photogeneration of 2-Deoxyribonolactone in Benzophenone−Purine Dyads. Formation of Ketyl−C1′ Biradicals. Organic Letters, 10(20), 4409-4412. doi:10.1021/ol801514vBelmadoui, N., Encinas, S., Climent, M. J., Gil, S., & Miranda, M. A. (2006). Intramolecular Interactions in the Triplet Excited States of Benzophenone–Thymine Dyads. Chemistry - A European Journal, 12(2), 553-561. doi:10.1002/chem.200500345Lhiaubet-Vallet, V., Boscá, F., & Miranda, M. A. (2007). Stereodifferentiating Drug−Biomolecule Interactions in the Triplet Excited State:  Studies on Supramolecular Carprofen/Protein Systems and on Carprofen−Tryptophan Model Dyads. The Journal of Physical Chemistry B, 111(2), 423-431. doi:10.1021/jp066968kVayá, I., Pérez-Ruiz, R., Lhiaubet-Vallet, V., Jiménez, M. C., & Miranda, M. A. (2010). Drug–protein interactions assessed by fluorescence measurements in the real complexes and in model dyads. Chemical Physics Letters, 486(4-6), 147-153. doi:10.1016/j.cplett.2009.12.091Seedher, N., & Bhatia, S. (2005). Mechanism of interaction of the non-steroidal antiinflammatory drugs meloxicam and nimesulide with serum albumin. Journal of Pharmaceutical and Biomedical Analysis, 39(1-2), 257-262. doi:10.1016/j.jpba.2005.02.031SEEDHER, N., & BHATIA, S. (2006). Reversible binding of celecoxib and valdecoxib with human serum albumin using fluorescence spectroscopic technique. Pharmacological Research, 54(2), 77-84. doi:10.1016/j.phrs.2006.02.008Nanda, R. K., Sarkar, N., & Banerjee, R. (2007). Probing the interaction of ellagic acid with human serum albumin: A fluorescence spectroscopic study. Journal of Photochemistry and Photobiology A: Chemistry, 192(2-3), 152-158. doi:10.1016/j.jphotochem.2007.05.018Zhou, B., Li, R., Zhang, Y., & Liu, Y. (2008). Kinetic analysis of the interaction between amphotericin B and human serum albumin using surface plasmon resonance and fluorescence spectroscopy. Photochemical & Photobiological Sciences, 7(4), 453. doi:10.1039/b717897bVahedian-Movahed, H., Saberi, M. R., & Chamani, J. (2011). Comparison of Binding Interactions of Lomefloxacin to Serum Albumin and Serum Transferrin by Resonance Light Scattering and Fluorescence Quenching Methods. Journal of Biomolecular Structure and Dynamics, 28(4), 483-502. doi:10.1080/07391102.2011.10508590Katrahalli, U., Kalalbandi, V. K. A., & Jaldappagari, S. (2012). The effect of anti-tubercular drug, ethionamide on the secondary structure of serum albumins: A biophysical study. Journal of Pharmaceutical and Biomedical Analysis, 59, 102-108. doi:10.1016/j.jpba.2011.09.013El-Kemary, M., Gil, M., & Douhal, A. (2007). Relaxation Dynamics of Piroxicam Structures within Human Serum Albumin Protein. Journal of Medicinal Chemistry, 50(12), 2896-2902. doi:10.1021/jm061421fTormo, L., Organero, J. A., Cohen, B., Martin, C., Santos, L., & Douhal, A. (2008). Dynamical and Structural Changes of an Anesthetic Analogue in Chemical and Biological Nanocavities. The Journal of Physical Chemistry B, 112(43), 13641-13647. doi:10.1021/jp803083yTardioli, S., Lammers, I., Hooijschuur, J.-H., Ariese, F., van der Zwan, G., & Gooijer, C. (2012). Complementary Fluorescence and Phosphorescence Study of the Interaction of Brompheniramine with Human Serum Albumin. The Journal of Physical Chemistry B, 116(24), 7033-7039. doi:10.1021/jp300055cVayá, I., Jiménez, M. C., & Miranda, M. A. (2007). Excited-State Interactions in Flurbiprofen−Tryptophan Dyads. The Journal of Physical Chemistry B, 111(31), 9363-9371. doi:10.1021/jp071301zCallis, P. R., & Burgess, B. K. (1997). Tryptophan Fluorescence Shifts in Proteins from Hybrid Simulations:  An Electrostatic Approach. The Journal of Physical Chemistry B, 101(46), 9429-9432. doi:10.1021/jp972436fLakowicz, J. R. (2000). On Spectral Relaxation in Proteins†¶‖. Photochemistry and Photobiology, 72(4), 421. doi:10.1562/0031-8655(2000)0722.0.co;2Schuler, B., & Eaton, W. A. (2008). Protein folding studied by single-molecule FRET. Current Opinion in Structural Biology, 18(1), 16-26. doi:10.1016/j.sbi.2007.12.003Shen, X., & Knutson, J. R. (2001). Subpicosecond Fluorescence Spectra of Tryptophan in Water. The Journal of Physical Chemistry B, 105(26), 6260-6265. doi:10.1021/jp010384vBeechem, J. M., & Brand, L. (1985). Time-Resolved Fluorescence of Proteins. Annual Review of Biochemistry, 54(1), 43-71. doi:10.1146/annurev.bi.54.070185.000355Callis, P. R. (1997). [7] 1La and 1Lb transitions of tryptophan: Applications of theory and experimental observations to fluorescence of proteins. Flourescence Spectroscopy, 113-150. doi:10.1016/s0076-6879(97)78009-1Basarić, N., & Wan, P. (2006). Competing Excited State Intramolecular Proton Transfer Pathways from Phenol to Anthracene Moieties. The Journal of Organic Chemistry, 71(7), 2677-2686. doi:10.1021/jo0524728Lukeman, M., & Wan, P. (2003). Excited-State Intramolecular Proton Transfer ino-Hydroxybiaryls:  A New Route to Dihydroaromatic Compounds. Journal of the American Chemical Society, 125(5), 1164-1165. doi:10.1021/ja029376yKeck, J., Kramer, H. E. A., Port, H., Hirsch, T., Fischer, P., & Rytz, G. (1996). Investigations on Polymeric and Monomeric Intramolecularly Hydrogen-Bridged UV Absorbers of the Benzotriazole and Triazine Class. The Journal of Physical Chemistry, 100(34), 14468-14475. doi:10.1021/jp961081hVollmer, F., & Rettig, W. (1996). Fluorescence loss mechanism due to large-amplitude motions in derivatives of 2,2′-bipyridyl exhibiting excited-state intramolecular proton transfer and perspectives of luminescence solar concentrators. Journal of Photochemistry and Photobiology A: Chemistry, 95(2), 143-155. doi:10.1016/1010-6030(95)04252-0Lukeman, M., & Wan, P. (2002). 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Effects of anisotropic interactions on the structure of animal groups

This paper proposes an agent-based model which reproduces different structures of animal groups. The shape and structure of the group is the effect of simple interaction rules among individuals: each animal deploys itself depending on the position of a limited number of close group mates. The proposed model is shown to produce clustered formations, as well as lines and V-like formations. The key factors which trigger the onset of different patterns are argued to be the relative strength of attraction and repulsion forces and, most important, the anisotropy in their application.Comment: 22 pages, 9 figures. Submitted. v1-v4: revised presentation; extended simulations; included technical results. v5: added a few clarification

On the duality between interaction responses and mutual positions in flocking and schooling.

Recent research in animal behaviour has contributed to determine how alignment, turning responses, and changes of speed mediate flocking and schooling interactions in different animal species. Here, we propose a complementary approach to the analysis of flocking phenomena, based on the idea that animals occupy preferential, anysotropic positions with respect to their neighbours, and devote a large amount of their interaction responses to maintaining their mutual positions. We test our approach by deriving the apparent alignment and attraction responses from simulated trajectories of animals moving side by side, or one in front of the other. We show that the anisotropic positioning of individuals, in combination with noise, is sufficient to reproduce several aspects of the movement responses observed in real animal groups. This anisotropy at the level of interactions should be considered explicitly in future models of flocking and schooling. By making a distinction between interaction responses involved in maintaining a preferred flock configuration, and interaction responses directed at changing it, our work provides a frame to discriminate movement interactions that signal directional conflict from interactions underlying consensual group motion

A unique cytotoxic CD4⁺ T cell-signature defines critical COVID-19

Objectives: SARS-CoV-2 infection causes a spectrum of clinical disease presentation, ranging from asymptomatic to fatal. While neutralising antibody (NAb) responses correlate with protection against symptomatic and severe infection, the contribution of the T-cell response to disease resolution or progression is still unclear. As newly emerging variants of concern have the capacity to partially escape NAb responses, defining the contribution of individual T-cell subsets to disease outcome is imperative to inform the development of next-generation COVID-19 vaccines. Methods: Immunophenotyping of T-cell responses in unvaccinated individuals was performed, representing the full spectrum of COVID-19 clinical presentation. Computational and manual analyses were used to identify T-cell populations associated with distinct disease states. Results: Critical SARS-CoV-2 infection was characterised by an increase in activated and cytotoxic CD4+ lymphocytes (CTL). These CD4+ CTLs were largely absent in asymptomatic to severe disease states. In contrast, non-critical COVID-19 was associated with high frequencies of naïve T cells and lack of activation marker expression. Conclusion: Highly activated and cytotoxic CD4+ T-cell responses may contribute to cell-mediated host tissue damage and progression of COVID-19. Induction of these potentially detrimental T-cell responses should be considered when developing and implementing effective COVID-19 control strategies

Quantifying the interplay between environmental and social effects on aggregated-fish dynamics

Demonstrating and quantifying the respective roles of social interactions and external stimuli governing fish dynamics is key to understanding fish spatial distribution. If seminal studies have contributed to our understanding of fish spatial organization in schools, little experimental information is available on fish in their natural environment, where aggregations often occur in the presence of spatial heterogeneities. Here, we applied novel modeling approaches coupled to accurate acoustic tracking for studying the dynamics of a group of gregarious fish in a heterogeneous environment. To this purpose, we acoustically tracked with submeter resolution the positions of twelve small pelagic fish (Selar crumenophthalmus) in the presence of an anchored floating object, constituting a point of attraction for several fish species. We constructed a field-based model for aggregated-fish dynamics, deriving effective interactions for both social and external stimuli from experiments. We tuned the model parameters that best fit the experimental data and quantified the importance of social interactions in the aggregation, providing an explanation for the spatial structure of fish aggregations found around floating objects. Our results can be generalized to other gregarious species and contexts as long as it is possible to observe the fine-scale movements of a subset of individuals.Comment: 10 pages, 5 figures and 4 supplementary figure

Bayesian Inference for Identifying Interaction Rules in Moving Animal Groups

The emergence of similar collective patterns from different self-propelled particle models of animal groups points to a restricted set of “universal” classes for these patterns. While universality is interesting, it is often the fine details of animal interactions that are of biological importance. Universality thus presents a challenge to inferring such interactions from macroscopic group dynamics since these can be consistent with many underlying interaction models. We present a Bayesian framework for learning animal interaction rules from fine scale recordings of animal movements in swarms. We apply these techniques to the inverse problem of inferring interaction rules from simulation models, showing that parameters can often be inferred from a small number of observations. Our methodology allows us to quantify our confidence in parameter fitting. For example, we show that attraction and alignment terms can be reliably estimated when animals are milling in a torus shape, while interaction radius cannot be reliably measured in such a situation. We assess the importance of rate of data collection and show how to test different models, such as topological and metric neighbourhood models. Taken together our results both inform the design of experiments on animal interactions and suggest how these data should be best analysed

Fluctuation-Driven Flocking Movement in Three Dimensions and Scale-Free Correlation

Recent advances in the study of flocking behavior have permitted more sophisticated analyses than previously possible. The concepts of “topological distances” and “scale-free correlations” are important developments that have contributed to this improvement. These concepts require us to reconsider the notion of a neighborhood when applied to theoretical models. Previous work has assumed that individuals interact with neighbors within a certain radius (called the “metric distance”). However, other work has shown that, assuming topological interactions, starlings interact on average with the six or seven nearest neighbors within a flock. Accounting for this observation, we previously proposed a metric-topological interaction model in two dimensions. The goal of our model was to unite these two interaction components, the metric distance and the topological distance, into one rule. In our previous study, we demonstrated that the metric-topological interaction model could explain a real bird flocking phenomenon called scale-free correlation, which was first reported by Cavagna et al. In this study, we extended our model to three dimensions while also accounting for variations in speed. This three-dimensional metric-topological interaction model displayed scale-free correlation for velocity and orientation. Finally, we introduced an additional new feature of the model, namely, that a flock can store and release its fluctuations

Active Brownian Particles. From Individual to Collective Stochastic Dynamics

We review theoretical models of individual motility as well as collective dynamics and pattern formation of active particles. We focus on simple models of active dynamics with a particular emphasis on nonlinear and stochastic dynamics of such self-propelled entities in the framework of statistical mechanics. Examples of such active units in complex physico-chemical and biological systems are chemically powered nano-rods, localized patterns in reaction-diffusion system, motile cells or macroscopic animals. Based on the description of individual motion of point-like active particles by stochastic differential equations, we discuss different velocity-dependent friction functions, the impact of various types of fluctuations and calculate characteristic observables such as stationary velocity distributions or diffusion coefficients. Finally, we consider not only the free and confined individual active dynamics but also different types of interaction between active particles. The resulting collective dynamical behavior of large assemblies and aggregates of active units is discussed and an overview over some recent results on spatiotemporal pattern formation in such systems is given.Comment: 161 pages, Review, Eur Phys J Special-Topics, accepte