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Artikel: AI algorithm for personalized resource allocation and treatment of hemorrhage casualties.

Jin, Xin / Frock, Andrew / Nagaraja, Sridevi / Wallqvist, Anders / Reifman, Jaques

2024 Band 15, Seite(n) 1327948

Abstract: A deep neural network-based artificial intelligence (AI) model was assessed for its utility in predicting vital signs of hemorrhage patients and optimizing the management of fluid resuscitation in mass casualties. With the use of a cardio-respiratory ... ...

Abstract	A deep neural network-based artificial intelligence (AI) model was assessed for its utility in predicting vital signs of hemorrhage patients and optimizing the management of fluid resuscitation in mass casualties. With the use of a cardio-respiratory computational model to generate synthetic data of hemorrhage casualties, an application was created where a limited data stream (the initial 10 min of vital-sign monitoring) could be used to predict the outcomes of different fluid resuscitation allocations 60 min into the future. The predicted outcomes were then used to select the optimal resuscitation allocation for various simulated mass-casualty scenarios. This allowed the assessment of the potential benefits of using an allocation method based on personalized predictions of future vital signs
Sprache	Englisch
Erscheinungsdatum	2024-01-25
Erscheinungsland	Switzerland
Dokumenttyp	Journal Article
ZDB-ID	2564217-0
ISSN	1664-042X
ISSN	1664-042X
DOI	10.3389/fphys.2024.1327948
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel: Predictive analytics identifies key factors driving hyperalgesic priming of muscle sensory neurons.

Nagaraja, Sridevi / Tewari, Shivendra G / Reifman, Jaques

Frontiers in neuroscience

2023 Band 17, Seite(n) 1254154

Abstract: Hyperalgesic priming, a form of neuroplasticity induced by inflammatory mediators, in peripheral nociceptors enhances the magnitude and duration of action potential (AP) firing to future inflammatory events and can potentially lead to pain chronification. ...

Abstract	Hyperalgesic priming, a form of neuroplasticity induced by inflammatory mediators, in peripheral nociceptors enhances the magnitude and duration of action potential (AP) firing to future inflammatory events and can potentially lead to pain chronification. The mechanisms underlying the development of hyperalgesic priming are not well understood, limiting the identification of novel therapeutic strategies to combat chronic pain. In this study, we used a computational model to identify key proteins whose modifications caused priming of muscle nociceptors and made them hyperexcitable to a subsequent inflammatory event. First, we extended a previously validated model of mouse muscle nociceptor sensitization to incorporate Epac-mediated interaction between two G protein-coupled receptor signaling pathways commonly activated by inflammatory mediators. Next, we calibrated and validated the model simulations of the nociceptor's AP response to both innocuous and noxious levels of mechanical force after two subsequent inflammatory events using literature data. Then, by performing global sensitivity analyses that simulated thousands of nociceptor-priming scenarios, we identified five ion channels and two molecular processes (from the 18 modeled transmembrane proteins and 29 intracellular signaling components) as potential regulators of the increase in AP firing in response to mechanical forces. Finally, when we simulated specific neuroplastic modifications in Kv1.1 and Nav1.7 alone as well as with simultaneous modifications in Nav1.7, Nav1.8, TRPA1, and Kv7.2, we observed a considerable increase in the fold change in the number of triggered APs in primed nociceptors. These results suggest that altering the expression of Kv1.1 and Nav1.7 might regulate the neuronal hyperexcitability in primed mechanosensitive muscle nociceptors.
Sprache	Englisch
Erscheinungsdatum	2023-10-24
Erscheinungsland	Switzerland
Dokumenttyp	Journal Article
ZDB-ID	2411902-7
ISSN	1662-453X ; 1662-4548
ISSN (online)	1662-453X
ISSN	1662-4548
DOI	10.3389/fnins.2023.1254154
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel: Identification of key factors driving inflammation-induced sensitization of muscle sensory neurons.

Nagaraja, Sridevi / Tewari, Shivendra G / Reifman, Jaques

Frontiers in neuroscience

2023 Band 17, Seite(n) 1147437

Abstract: Sensory neurons embedded in muscle tissue that initiate pain sensations, i.e., nociceptors, are temporarily sensitized by inflammatory mediators during musculoskeletal trauma. These neurons transduce peripheral noxious stimuli into an electrical signal [ ... ...

Abstract	Sensory neurons embedded in muscle tissue that initiate pain sensations, i.e., nociceptors, are temporarily sensitized by inflammatory mediators during musculoskeletal trauma. These neurons transduce peripheral noxious stimuli into an electrical signal [i.e., an action potential (AP)] and, when sensitized, demonstrate lower activation thresholds and a heightened AP response. We still do not understand the relative contributions of the various transmembrane proteins and intracellular signaling processes that drive the inflammation-induced hyperexcitability of nociceptors. In this study, we used computational analysis to identify key proteins that could regulate the inflammation-induced increase in the magnitude of AP firing in mechanosensitive muscle nociceptors. First, we extended a previously validated model of a mechanosensitive mouse muscle nociceptor to incorporate two inflammation-activated G protein-coupled receptor (GPCR) signaling pathways and validated the model simulations of inflammation-induced nociceptor sensitization using literature data. Then, by performing global sensitivity analyses that simulated thousands of inflammation-induced nociceptor sensitization scenarios, we identified three ion channels and four molecular processes (from the 17 modeled transmembrane proteins and 28 intracellular signaling components) as potential regulators of the inflammation-induced increase in AP firing in response to mechanical forces. Moreover, we found that simulating single knockouts of transient receptor potential ankyrin 1 (TRPA1) and reducing the rates of G
Sprache	Englisch
Erscheinungsdatum	2023-05-12
Erscheinungsland	Switzerland
Dokumenttyp	Journal Article
ZDB-ID	2411902-7
ISSN	1662-453X ; 1662-4548
ISSN (online)	1662-453X
ISSN	1662-4548
DOI	10.3389/fnins.2023.1147437
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel ; Online: Development and validation of a mathematical model to simulate human cardiovascular and respiratory responses to battlefield trauma.

Jin, Xin / Laxminarayan, Srinivas / Nagaraja, Sridevi / Wallqvist, Anders / Reifman, Jaques

International journal for numerical methods in biomedical engineering

2022 Band 39, Heft 1, Seite(n) e3662

Abstract: Mathematical models of human cardiovascular and respiratory systems provide a viable alternative to generate synthetic data to train artificial intelligence (AI) clinical decision-support systems and assess closed-loop control technologies, for military ... ...

Abstract	Mathematical models of human cardiovascular and respiratory systems provide a viable alternative to generate synthetic data to train artificial intelligence (AI) clinical decision-support systems and assess closed-loop control technologies, for military medical applications. However, existing models are either complex, standalone systems that lack the interface to other applications or fail to capture the essential features of the physiological responses to the major causes of battlefield trauma (i.e., hemorrhage and airway compromise). To address these limitations, we developed the cardio-respiratory (CR) model by expanding and integrating two previously published models of the cardiovascular and respiratory systems. We compared the vital signs predicted by the CR model with those from three models, using experimental data from 27 subjects in five studies, involving hemorrhage, fluid resuscitation, and respiratory perturbations. Overall, the CR model yielded relatively small root mean square errors (RMSEs) for mean arterial pressure (MAP; 20.88 mm Hg), end-tidal CO
Mesh-Begriff(e)	Humans ; Artificial Intelligence ; Lung ; Hemorrhage ; Arterial Pressure/physiology ; Models, Theoretical
Sprache	Englisch
Erscheinungsdatum	2022-11-25
Erscheinungsland	England
Dokumenttyp	Journal Article ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	2540968-2
ISSN	2040-7947 ; 2040-7939
ISSN (online)	2040-7947
ISSN	2040-7939
DOI	10.1002/cnm.3662
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel: In silico

Nagaraja, Sridevi / Queme, Luis F / Hofmann, Megan C / Tewari, Shivendra G / Jankowski, Michael P / Reifman, Jaques

Frontiers in neuroscience

2021 Band 15, Seite(n) 719735

Abstract: Nociceptive nerve endings embedded in muscle tissue transduce peripheral noxious stimuli into an electrical signal [i.e., an action potential (AP)] to initiate pain sensations. A major contributor to nociception from the muscles is mechanosensation. ... ...

Abstract	Nociceptive nerve endings embedded in muscle tissue transduce peripheral noxious stimuli into an electrical signal [i.e., an action potential (AP)] to initiate pain sensations. A major contributor to nociception from the muscles is mechanosensation. However, due to the heterogeneity in the expression of proteins, such as ion channels, pumps, and exchangers, on muscle nociceptors, we currently do not know the relative contributions of different proteins and signaling molecules to the neuronal response due to mechanical stimuli. In this study, we employed an integrated approach combining a customized experimental study in mice with a computational model to identify key proteins that regulate mechanical nociception in muscles. First, using newly collected data from somatosensory recordings in mouse hindpaw muscles, we developed and then validated a computational model of a mechanosensitive mouse muscle nociceptor. Next, by performing global sensitivity analyses that simulated thousands of nociceptors, we identified three ion channels (among the 17 modeled transmembrane proteins and four endoplasmic reticulum proteins) as potential regulators of the nociceptor response to mechanical forces in both the innocuous and noxious range. Moreover, we found that simulating single knockouts of any of the three ion channels, delayed rectifier voltage-gated K
Sprache	Englisch
Erscheinungsdatum	2021-09-10
Erscheinungsland	Switzerland
Dokumenttyp	Journal Article
ZDB-ID	2411902-7
ISSN	1662-453X ; 1662-4548
ISSN (online)	1662-453X
ISSN	1662-4548
DOI	10.3389/fnins.2021.719735
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel: Predictive Approach Identifies Molecular Targets and Interventions to Restore Angiogenesis in Wounds With Delayed Healing.

Nagaraja, Sridevi / Chen, Lin / DiPietro, Luisa A / Reifman, Jaques / Mitrophanov, Alexander Y

Frontiers in physiology

2019 Band 10, Seite(n) 636

Abstract: Impaired angiogenesis is a hallmark of wounds with delayed healing, and currently used therapies to restore angiogenesis have limited efficacy. Here, we employ a computational simulation-based approach to identify influential molecular and cellular ... ...

Abstract	Impaired angiogenesis is a hallmark of wounds with delayed healing, and currently used therapies to restore angiogenesis have limited efficacy. Here, we employ a computational simulation-based approach to identify influential molecular and cellular processes, as well as protein targets, whose modulation may stimulate angiogenesis in wounds. We developed a mathematical model that captures the time courses for platelets, 9 cell types, 29 proteins, and oxygen, which are involved in inflammation, proliferation, and angiogenesis during wound healing. We validated our model using previously published experimental data. By performing global sensitivity analysis on thousands of simulated wound-healing scenarios, we identified six processes (among the 133 modeled in total) whose modulation may improve angiogenesis in wounds. By simulating knockouts of 25 modeled proteins and by simulating different wound-oxygenation levels, we identified four proteins [namely, transforming growth factor (TGF)-β, vascular endothelial growth factor (VEGF), fibroblast growth factor-2 (FGF-2), and angiopoietin-2 (ANG-2)], as well as oxygen, as therapeutic targets for stimulating angiogenesis in wounds. Our modeling results indicated that simultaneous inhibition of TGF-β and supplementation of either FGF-2 or ANG-2 could be more effective in stimulating wound angiogenesis than the modulation of either protein alone. Our findings suggest experimentally testable intervention strategies to restore angiogenesis in wounds with delayed healing.
Sprache	Englisch
Erscheinungsdatum	2019-05-28
Erscheinungsland	Switzerland
Dokumenttyp	Journal Article
ZDB-ID	2564217-0
ISSN	1664-042X
ISSN	1664-042X
DOI	10.3389/fphys.2019.00636
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel ; Online: Computational Identification of Mechanistic Factors That Determine the Timing and Intensity of the Inflammatory Response.

Sridevi Nagaraja / Jaques Reifman / Alexander Y Mitrophanov

PLoS Computational Biology, Vol 11, Iss 12, p e

2015 Band 1004460

Abstract: Timely resolution of inflammation is critical for the restoration of homeostasis in injured or infected tissue. Chronic inflammation is often characterized by a persistent increase in the concentrations of inflammatory cells and molecular mediators, ... ...

Abstract	Timely resolution of inflammation is critical for the restoration of homeostasis in injured or infected tissue. Chronic inflammation is often characterized by a persistent increase in the concentrations of inflammatory cells and molecular mediators, whose distinct amount and timing characteristics offer an opportunity to identify effective therapeutic regulatory targets. Here, we used our recently developed computational model of local inflammation to identify potential targets for molecular interventions and to investigate the effects of individual and combined inhibition of such targets. This was accomplished via the development and application of computational strategies involving the simulation and analysis of thousands of inflammatory scenarios. We found that modulation of macrophage influx and efflux is an effective potential strategy to regulate the amount of inflammatory cells and molecular mediators in both normal and chronic inflammatory scenarios. We identified three molecular mediators - tumor necrosis factor-α (TNF-α), transforming growth factor-β (TGF-β), and the chemokine CXCL8 - as potential molecular targets whose individual or combined inhibition may robustly regulate both the amount and timing properties of the kinetic trajectories for neutrophils and macrophages in chronic inflammation. Modulation of macrophage flux, as well as of the abundance of TNF-α, TGF-β, and CXCL8, may improve the resolution of chronic inflammation.
Schlagwörter	Biology (General) ; QH301-705.5
Thema/Rubrik (Code)	610
Sprache	Englisch
Erscheinungsdatum	2015-12-01T00:00:00Z
Verlag	Public Library of Science (PLoS)
Dokumenttyp	Artikel ; Online
Datenquelle	BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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Artikel ; Online: Computational Identification of Mechanistic Factors That Determine the Timing and Intensity of the Inflammatory Response.

Nagaraja, Sridevi / Reifman, Jaques / Mitrophanov, Alexander Y

PLoS computational biology

2015 Band 11, Heft 12, Seite(n) e1004460

Abstract	Timely resolution of inflammation is critical for the restoration of homeostasis in injured or infected tissue. Chronic inflammation is often characterized by a persistent increase in the concentrations of inflammatory cells and molecular mediators, whose distinct amount and timing characteristics offer an opportunity to identify effective therapeutic regulatory targets. Here, we used our recently developed computational model of local inflammation to identify potential targets for molecular interventions and to investigate the effects of individual and combined inhibition of such targets. This was accomplished via the development and application of computational strategies involving the simulation and analysis of thousands of inflammatory scenarios. We found that modulation of macrophage influx and efflux is an effective potential strategy to regulate the amount of inflammatory cells and molecular mediators in both normal and chronic inflammatory scenarios. We identified three molecular mediators - tumor necrosis factor-α (TNF-α), transforming growth factor-β (TGF-β), and the chemokine CXCL8 - as potential molecular targets whose individual or combined inhibition may robustly regulate both the amount and timing properties of the kinetic trajectories for neutrophils and macrophages in chronic inflammation. Modulation of macrophage flux, as well as of the abundance of TNF-α, TGF-β, and CXCL8, may improve the resolution of chronic inflammation.
Mesh-Begriff(e)	Animals ; Computer Simulation ; Humans ; Immunity, Innate/immunology ; Inflammation/immunology ; Inflammation/pathology ; Interleukin-8/immunology ; Macrophage Activation/immunology ; Macrophages/immunology ; Models, Immunological ; Severity of Illness Index ; Transforming Growth Factor beta/immunology ; Tumor Necrosis Factor-alpha/immunology
Chemische Substanzen	Interleukin-8 ; Transforming Growth Factor beta ; Tumor Necrosis Factor-alpha
Sprache	Englisch
Erscheinungsdatum	2015-12-03
Erscheinungsland	United States
Dokumenttyp	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2193340-6
ISSN	1553-7358 ; 1553-734X
ISSN (online)	1553-7358
ISSN	1553-734X
DOI	10.1371/journal.pcbi.1004460
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel ; Online: Computational analysis identifies putative prognostic biomarkers of pathological scarring in skin wounds.

Nagaraja, Sridevi / Chen, Lin / DiPietro, Luisa A / Reifman, Jaques / Mitrophanov, Alexander Y

Journal of translational medicine

2018 Band 16, Heft 1, Seite(n) 32

Abstract: Background: Pathological scarring in wounds is a prevalent clinical outcome with limited prognostic options. The objective of this study was to investigate whether cellular signaling proteins could be used as prognostic biomarkers of pathological ... ...

Abstract	Background: Pathological scarring in wounds is a prevalent clinical outcome with limited prognostic options. The objective of this study was to investigate whether cellular signaling proteins could be used as prognostic biomarkers of pathological scarring in traumatic skin wounds. Methods: We used our previously developed and validated computational model of injury-initiated wound healing to simulate the time courses for platelets, 6 cell types, and 21 proteins involved in the inflammatory and proliferative phases of wound healing. Next, we analysed thousands of simulated wound-healing scenarios to identify those that resulted in pathological (i.e., excessive) scarring. Then, we identified candidate proteins that were elevated (or decreased) at the early stages of wound healing in those simulations and could therefore serve as predictive biomarkers of pathological scarring outcomes. Finally, we performed logistic regression analysis and calculated the area under the receiver operating characteristic curve to quantitatively assess the predictive accuracy of the model-identified putative biomarkers. Results: We identified three proteins (interleukin-10, tissue inhibitor of matrix metalloproteinase-1, and fibronectin) whose levels were elevated in pathological scars as early as 2 weeks post-wounding and could predict a pathological scarring outcome occurring 40 days after wounding with 80% accuracy. Conclusion: Our method for predicting putative prognostic wound-outcome biomarkers may serve as an effective means to guide the identification of proteins predictive of pathological scarring.
Mesh-Begriff(e)	Biomarkers/metabolism ; Cicatrix/diagnosis ; Cicatrix/pathology ; Computational Biology/methods ; Humans ; Kinetics ; Logistic Models ; Prognosis ; ROC Curve ; Skin/pathology ; Wound Healing
Chemische Substanzen	Biomarkers
Sprache	Englisch
Erscheinungsdatum	2018-02-20
Erscheinungsland	England
Dokumenttyp	Journal Article ; Research Support, U.S. Gov't, Non-P.H.S.
ISSN	1479-5876
ISSN (online)	1479-5876
DOI	10.1186/s12967-018-1406-x
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel ; Online: Computational analysis identifies putative prognostic biomarkers of pathological scarring in skin wounds

Sridevi Nagaraja / Lin Chen / Luisa A. DiPietro / Jaques Reifman / Alexander Y. Mitrophanov

Journal of Translational Medicine, Vol 16, Iss 1, Pp 1-

2018 Band 13

Abstract: Abstract Background Pathological scarring in wounds is a prevalent clinical outcome with limited prognostic options. The objective of this study was to investigate whether cellular signaling proteins could be used as prognostic biomarkers of pathological ...

Abstract	Abstract Background Pathological scarring in wounds is a prevalent clinical outcome with limited prognostic options. The objective of this study was to investigate whether cellular signaling proteins could be used as prognostic biomarkers of pathological scarring in traumatic skin wounds. Methods We used our previously developed and validated computational model of injury-initiated wound healing to simulate the time courses for platelets, 6 cell types, and 21 proteins involved in the inflammatory and proliferative phases of wound healing. Next, we analysed thousands of simulated wound-healing scenarios to identify those that resulted in pathological (i.e., excessive) scarring. Then, we identified candidate proteins that were elevated (or decreased) at the early stages of wound healing in those simulations and could therefore serve as predictive biomarkers of pathological scarring outcomes. Finally, we performed logistic regression analysis and calculated the area under the receiver operating characteristic curve to quantitatively assess the predictive accuracy of the model-identified putative biomarkers. Results We identified three proteins (interleukin-10, tissue inhibitor of matrix metalloproteinase-1, and fibronectin) whose levels were elevated in pathological scars as early as 2 weeks post-wounding and could predict a pathological scarring outcome occurring 40 days after wounding with 80% accuracy. Conclusion Our method for predicting putative prognostic wound-outcome biomarkers may serve as an effective means to guide the identification of proteins predictive of pathological scarring.
Schlagwörter	Pathological scarring ; Computational modeling ; Biomarkers ; Predictive analysis ; Medicine ; R
Thema/Rubrik (Code)	616
Sprache	Englisch
Erscheinungsdatum	2018-02-01T00:00:00Z
Verlag	BMC
Dokumenttyp	Artikel ; Online
Datenquelle	BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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