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Strube LF, Elgart S, Childs LM. Infection-induced increases to population size during cycles in a discrete-time epidemic model. J Math Biol 2024; 88:60. [PMID: 38600396 PMCID: PMC11006791 DOI: 10.1007/s00285-024-02074-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Revised: 11/11/2023] [Accepted: 02/18/2024] [Indexed: 04/12/2024]
Abstract
One-dimensional discrete-time population models, such as those that involve Logistic or Ricker growth, can exhibit periodic and chaotic dynamics. Expanding the system by one dimension to incorporate epidemiological interactions causes an interesting complexity of new behaviors. Here, we examine a discrete-time two-dimensional susceptible-infectious (SI) model with Ricker growth and show that the introduction of infection can not only produce a distinctly different bifurcation structure than that of the underlying disease-free system but also lead to counter-intuitive increases in population size. We use numerical bifurcation analysis to determine the influence of infection on the location and types of bifurcations. In addition, we examine the appearance and extent of a phenomenon known as the 'hydra effect,' i.e., increases in total population size when factors, such as mortality, that act negatively on a population, are increased. Previous work, primarily focused on dynamics at fixed points, showed that the introduction of infection that reduces fecundity to the SI model can lead to a so-called 'infection-induced hydra effect.' Our work shows that even in such a simple two-dimensional SI model, the introduction of infection that alters fecundity or mortality can produce dynamics can lead to the appearance of a hydra effect, particularly when the disease-free population is at a cycle.
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Affiliation(s)
- Laura F Strube
- Department of Mathematics, Virginia Tech, 225 Stanger St, Blacksburg, VA, 24061, USA
- Department of Immunology, University of Pittsburgh Medical School, The Assembly, 5051 Centre Avenue, Pittsburgh, PA, 15213, USA
- Department of Computational and Systems Biology, University of Pittsburgh Medical School, 800 Murdoch I building, 3420 Forbes Avenue, Pittsburgh, PA, 15213, USA
| | - Shoshana Elgart
- Laurel Springs School, 302 El Paseo Rd, Ojai, CA, 93023, USA
| | - Lauren M Childs
- Department of Mathematics, Virginia Tech, 225 Stanger St, Blacksburg, VA, 24061, USA.
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2
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Panja S, Truica MI, Yu CY, Saggurthi V, Craige MW, Whitehead K, Tuiche MV, Al-Saadi A, Vyas R, Ganesan S, Gohel S, Coffman F, Parrott JS, Quan S, Jha S, Kim I, Schaeffer E, Kothari V, Abdulkadir SA, Mitrofanova A. Mechanism-centric regulatory network identifies NME2 and MYC programs as markers of Enzalutamide resistance in CRPC. Nat Commun 2024; 15:352. [PMID: 38191557 PMCID: PMC10774320 DOI: 10.1038/s41467-024-44686-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2022] [Accepted: 12/22/2023] [Indexed: 01/10/2024] Open
Abstract
Heterogeneous response to Enzalutamide, a second-generation androgen receptor signaling inhibitor, is a central problem in castration-resistant prostate cancer (CRPC) management. Genome-wide systems investigation of mechanisms that govern Enzalutamide resistance promise to elucidate markers of heterogeneous treatment response and salvage therapies for CRPC patients. Focusing on the de novo role of MYC as a marker of Enzalutamide resistance, here we reconstruct a CRPC-specific mechanism-centric regulatory network, connecting molecular pathways with their upstream transcriptional regulatory programs. Mining this network with signatures of Enzalutamide response identifies NME2 as an upstream regulatory partner of MYC in CRPC and demonstrates that NME2-MYC increased activities can predict patients at risk of resistance to Enzalutamide, independent of co-variates. Furthermore, our experimental investigations demonstrate that targeting MYC and its partner NME2 is beneficial in Enzalutamide-resistant conditions and could provide an effective strategy for patients at risk of Enzalutamide resistance and/or for patients who failed Enzalutamide treatment.
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Affiliation(s)
- Sukanya Panja
- Department of Health Informatics, Rutgers School of Health Professions, Newark, NJ, 07107, USA
| | - Mihai Ioan Truica
- Department of Urology, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA
| | - Christina Y Yu
- Department of Health Informatics, Rutgers School of Health Professions, Newark, NJ, 07107, USA
| | - Vamshi Saggurthi
- Department of Health Informatics, Rutgers School of Health Professions, Newark, NJ, 07107, USA
| | - Michael W Craige
- Department of Health Informatics, Rutgers School of Health Professions, Newark, NJ, 07107, USA
| | - Katie Whitehead
- Department of Health Informatics, Rutgers School of Health Professions, Newark, NJ, 07107, USA
| | - Mayra V Tuiche
- Department of Health Informatics, Rutgers School of Health Professions, Newark, NJ, 07107, USA
- Rutgers Biomedical and Health Sciences, Rutgers School of Graduate Studies, Newark, NJ, 07039, USA
| | - Aymen Al-Saadi
- Department of Electrical and Computer Engineering, Rutgers School of Engineering, New Brunswick, NJ, 08854, USA
| | - Riddhi Vyas
- Department of Health Informatics, Rutgers School of Health Professions, Newark, NJ, 07107, USA
| | - Shridar Ganesan
- Rutgers Cancer Institute of New Jersey, New Brunswick, NJ, 08901, USA
| | - Suril Gohel
- Department of Health Informatics, Rutgers School of Health Professions, Newark, NJ, 07107, USA
| | - Frederick Coffman
- Department of Health Informatics, Rutgers School of Health Professions, Newark, NJ, 07107, USA
| | - James S Parrott
- Department of Health Informatics, Rutgers School of Health Professions, Newark, NJ, 07107, USA
| | - Songhua Quan
- Department of Urology, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA
| | - Shantenu Jha
- Department of Electrical and Computer Engineering, Rutgers School of Engineering, New Brunswick, NJ, 08854, USA
| | - Isaac Kim
- Rutgers Cancer Institute of New Jersey, New Brunswick, NJ, 08901, USA
- Department of Urology, Yale School of Medicine, New Heaven, CT, 06510, USA
| | - Edward Schaeffer
- Department of Urology, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA
| | - Vishal Kothari
- Department of Urology, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA.
| | - Sarki A Abdulkadir
- Department of Urology, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA.
- Robert H. Lurie Comprehensive Cancer Center, Chicago, IL, 60611, USA.
| | - Antonina Mitrofanova
- Department of Health Informatics, Rutgers School of Health Professions, Newark, NJ, 07107, USA.
- Rutgers Cancer Institute of New Jersey, New Brunswick, NJ, 08901, USA.
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Jaramillo JM, Ma J, van den Driessche P, Yakubu AA. Disease-Induced Hydra Effect with Overcompensatory Recruitment. Bull Math Biol 2021; 84:17. [PMID: 34923617 DOI: 10.1007/s11538-021-00975-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Accepted: 11/18/2021] [Indexed: 11/27/2022]
Abstract
In ecological systems, the hydra effect is an increase in population size caused by an increase in mortality. This seemingly counterintuitive effect has been observed in several populations, including fish, blowflies, snails and plants, and has been modeled in both continuous and discrete time. A similar effect induced by disease has recently been observed empirically. Here we present theoretical and simulation results for an infectious disease-induced hydra effect, namely conditions under which the total population size, composed of those that are infectious as well as those that are susceptible, at an endemic equilibrium is greater than the population size at the disease-free equilibrium. (For an endemic k-cycle, this can be similarly defined using the average population.) We find this disease-induced hydra effect occurs when the intra-specific competition is strong and disease infection sufficiently inhibits the reproductive output of infected individuals. For our continuous time model, we give a necessary and sufficient condition for a disease-induced hydra effect. This condition requires overcompensatory recruitment. With a discrete time model, we show there is no disease-induced hydra effect without overcompensatory recruitment. We illustrate by simulations that a disease-induced hydra effect may occur with Ricker recruitment when the endemic system converges to either a fixed equilibrium or a 2-cycle.
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Affiliation(s)
- J M Jaramillo
- Department of Mathematics and Statistics, University of Victoria, Victoria, BC, V8W 2Y2, Canada.
| | - Junling Ma
- Department of Mathematics and Statistics, University of Victoria, Victoria, BC, V8W 2Y2, Canada
| | - P van den Driessche
- Department of Mathematics and Statistics, University of Victoria, Victoria, BC, V8W 2Y2, Canada
| | - Abdul-Aziz Yakubu
- Department of Mathematics, Howard University, Washington, DC, 20059, USA
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da S Costa MI, Anjos LD. The interplay between fishery yield and top predator culling in a multispecies fishery context. MATHEMATICAL MEDICINE AND BIOLOGY : A JOURNAL OF THE IMA 2020; 37:351-363. [PMID: 31930337 DOI: 10.1093/imammb/dqz017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/06/2019] [Revised: 10/23/2019] [Accepted: 11/24/2019] [Indexed: 06/10/2023]
Abstract
In food webs, fishery can play the role of top predator, competing thus with other top predators for valuable food resources. In this view, it has been claimed in fisheries management that culling of top predators can be a means to improve fishery yield. To investigate this hypothesis, we use theoretical population models to assess in a multispecies context how fishery yield from target species harvest responds to top predator cull. Defying crisp summary, the four analysed food web models show that this response may be either positive or negative or both, indicating that in terms of multispecies fishery management the harvest yield may not accrue as a consequence of predator removal. In addition, this multitude of behaviours points also to the fact that the response of fishery yield to top predator cull may be difficult to assess.
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Affiliation(s)
- Michel Iskin da S Costa
- Laboratório Nacional de Computação Científica, Av. Getúlio Vargas, 333 - Quitandinha, Petrópolis, RJ 25651-070 Brazil Corresponding author.
| | - Lucas Dos Anjos
- Laboratório Nacional de Computação Científica, Av. Getúlio Vargas, 333 - Quitandinha, Petrópolis, RJ 25651-070 Brazil Corresponding author.
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