Journal Publications (* indicates equal contributions)

  1. A. Khang, Q. Nguyen, X. Feng, D. P. Howsmon, and M. S. Sacks, “Three-dimensional analysis of aortic valve interstitial cell shape and its relation to contractile behavior,” Acta Biomateriala, vol. 163, pp. 194–209, Jun. 2023. doi: 10.1016/j.actbio.2022.01.039

  2. T. M. West, D. P. Howsmon, M. W. Messida, H. N. Vo, A. A. Janobas, A. B. Baker, and M. S. Sacks, “The effects of strain rate and level on aortic valve interstitial cell activation in a 3D hydrogel,” APL Bioengineering, vol. 7, no. 2, p. 026 101, 2023. doi: 10.1063/5.0138030

  3. L. Bansal, E.-M. Nichols, D. P. Howsmon, J. Neisen, F. Cunningham, S. Petit-Frere, S. Ludbrook, and V. Damian, “Mathematical modeling of complement pathway dynamics for target validation and selection of drug modalities for complement therapies,” Frontiers in Pharmacology, vol. 13, p. 855 743, Apr. 2022. doi: 10.3389/fphar.2022.855743

  4. A. Khang* , E. M. Lejeune* , A. Abbaspour, D. P. Howsmon, and M. S. Sacks, “On the 3D correlation between myofibroblast shape and contraction,” Journal of Biomechanical Engineering, vol. 143, no. 9, p. 094 503, Sep. 2021. doi: 10.1115/1.4050915

  5. E. Castillero, D. P. Howsmon, B. V. Rego, Y. Xue, C. Camillo, S. Keeney, K. H. Driesbaugh, T. Kawashima, I. George, R. C. Gorman, J. H. Gorman III, M. S. Sacks, R. J. Levy, and G. Ferrari, “Altered responsiveness to TGF-β and BMP and increased CD45+ cell presence in mitral valves are unique features of ischemic mitral regurgitation,” Arteriosclerosis, Thrombosis, and Vascular Biology, vol. 41, no. 6, pp. 2049–2062, Jun. 2021. doi: 10.1161/ATVBAHA.121.316111

  6. D. P. Howsmon and M. S. Sacks, “On valve interstital cell signaling: The link between multiscale mechanics and mechanobiology,” Cardiovascular Engineering and Technology, vol. 12, pp. 15–27, Feb. 2021. doi: 10. 1007/s13239-020-00509-4

  7. K. M. Kodigepalli, K. Thatcher, T. West, D. P. Howsmon, F. J. Schoen, M. S. Sacks, C. K. Breuer, and J. Lincoln, “Biology and biomechanics of heart valve extracellular matrix,” Journal of Cardiovascular Development and Disease, vol. 7, no. 4, p. 57, Dec. 2020. doi: 10.3390/jcdd7040057

  8. S. Ayoub, D. P. Howsmon, C.-H. Lee, and M. S. Sacks, “On the role of predicted mitral valve interstitial cell deformation on its biosynthetic behavior,” Biomechanics and Modeling in Mechanobiology, Aug. 2020. doi: 10.1007/s10237-020-01373-w

  9. D. P. Howsmon* , B. V. Rego* , E. Castillero, S. Ayoub, A. H. Khalighi, R. C. Gorman, J. H. Gorman III, G. Ferrari, and M. S. Sacks, “Mitral valve leaflet response to ischaemic mitral regurgitation: From gene expression to tissue remodeling,” Journal of the Royal Society Interface, vol. 17, no. 165, p. 20 200 098, May 2020. doi: 10.1098/rsif.2020.0098

  10. D. P. Howsmon* , S. M. Quinn* , J. Hahn, and S. P. Gilbert, “Kinesin-2 heterodimerization alters catalytic properties to control entry into the processive run,” Journal of Biological Chemistry, vol. 293, no. 35, pp. 13 389– 13 400, Jul. 2018. doi: 10.1074/jbc.RA118.002767

  11. D. P. Howsmon, T. Vargason, R. A. Rubin, S. Melnyk, S. J. James, R. Frye, and J. Hahn, “Multivariate techniques enablea biochemical classification of children with autism spectrum disorder versus typically-developing peers: A comparison and validation study,” Bioengineering and Translational Medicine, vol. 3, no. 2, pp. 156– 165, May 2018. doi: 10.1002/btm2.10095

  12. T. Vargason, D. P. Howsmon, and J. Hahn, “From data to diagnosis: The search for biochemical markers of autism spectrum disorder,” Chemical Engineering Progress, vol. 114, no. 5, pp. 40–45, May 2018

  13. G. P. Forlenza, F. M. Cameron, T. T. Ly, D. Lam, D. P. Howsmon, N. Baysal, G. Kulina, L. Messer, P. Clinton, C. Levister, S. D. Patek, C. J. Levy, R. P. Wadwa, D. M. Maahs, B. W. Bequette, and B. A. Buckingham, “Fully closed-loop multiple model probabilistic predictive controller artificial pancreas performance in adolescents and adults in a supervised hotel setting,” Diabetes Technology & Therapeutics, vol. 20, no. 5, pp. 335–343, May 2018. doi: 10.1089/dia.2017.0424

  14. D. P. Howsmon, N. Baysal, B. A. Buckingham, G. P. Forlenza, T. T. Ly, D. M. Maahs, T. Marcal, L. Towers, E. Mauritzen, S. Deshpande, L. M. Huyett, J. E. Pinsker, R. Gondhalekar, F. J. Doyle III, E. Dassau, J. Hahn, and B. W. Bequette, “Real-time detection of infusion site failures in a closed-loop artificial pancreas,” Journal of Diabetes Science and Technology, vol. 12, no. 3, May 2018. doi: 10.1177/1932296818755173

  15. D. P. Howsmon, J. B. Adams, U. Kruger, E. Geis, E. Gehn, and J. Hahn, “Erythrocyte fatty acid profiles in children are not predictive of autism spectrum disorder status: A case control study,” Biomarker Research, vol. 6, p. 12, Mar. 2018. doi: 10.1186/s40364-018-0125-z

  16. D.-W. Kang, Z. E. Ilhan, N. G. Isern, D. W. Hoyt, D. P. Howsmon, M. Shaffer, C. A. Lozupone, J. Hahn, J. B. Adams, and R. Krajmalnik-Brown, “Differences in fecal microbial metabolites and microbiota of children with autism spectrum disorders,” Anaerobe, vol. 49, pp. 121–131, Feb. 2018. doi: 10.1016/j.anaerobe.2017. 12.007

  17. D. P. Howsmon* , S. Steinmeyer* , R. C. Alaniz, J. Hahn, and A. Jayaraman, “Empirical modeling of t cell activation predicts interplay of host cytokines and bacterial indole,” Biotechnology and Bioengineering, vol. 114, no. 11, pp. 2660–2667, Nov. 2017. doi: 10.1002/bit.26371

  18. F. M. Cameron, T. T. Ly, B. A. Buckingham, D. M. Maahs, G. P. Forlenza, C. J. Levy, D. Lam, P. Clinton, L. H. Messer, E. Westfall, C. Levister, Y. Y. Xie, N. Baysal, D. Howsmon, S. D. Patek, and B. W. Bequette, “Closed-loop control without meal announcement in type 1 diabetes,” Diabetes Technology & Therapeutics, vol. 19, no. 9, pp. 527–532, Aug. 2017. doi: 10.1089/dia.2017.0078

  19. G. P. Forlenza* , S. Deshpande* , T. T. Ly, D. P. Howsmon, F. Cameron, N. Baysal, E. Mauritzen, T. Marcal, L. Towers, B. W. Bequette, L. M. Huyett, J. E. Pinsker, R. Gondhalekar, F. J. Doyle, D. M. Maahs, B. A. Buckingham, and E. Dassau, “Application of zone model predictive control artificial pancreas during extended use of infusion set and sensor: A randomized crossover-controlled home-use trial,” Diabetes Care, p. dc170500, Jun. 2017. doi: 10.2337/dc17-0500

  20. T. Vargason, D. P. Howsmon, D. L. McGuinness, and J. Hahn, “On the use of multivariate methods for analysis of data from biological networks,” Processes, vol. 5, no. 3, p. 36, Jul. 2017. doi: 10.3390/pr5030036

  21. D. P. Howsmon, U. Kruger, S. Melnyk, S. J. James, and J. Hahn, “Classification and adaptive behavior prediction of children with autism spectrum disorder based upon multivariate data analysis of markers of oxidative stress and DNA methylation,” PLoS Computational Biology, vol. 13, no. 3, e1005385, Mar. 2017. doi: 10.1371/journal.pcbi.1005385

  22. T. Vargason, D. P. Howsmon, S. Melnyk, S. J. James, and J. Hahn, “Mathematical modeling of the methionine cycle and transsulfuration pathway in individuals with autism spectrum disorder,” Journal of Theoretical Biology, vol. 416, pp. 28–37, Mar. 2017. doi: 10.1016/j.jtbi.2016.12.021

  23. D. P. Howsmon, F. Cameron, N. Baysal, T. T. Ly, G. P. Forlenza, D. M. Maahs, B. A. Buckingham, J. Hahn, and B. W. Bequette, “Continuous glucose monitoring enables the detection of losses in infusion set actuation (LISAs),” Sensors, vol. 17, no. 1, p. 161, Jan. 2017. doi: 10.3390/s17010161

  24. J. Adams, D. P. Howsmon, U. Kruger, E. Geis, E. Gehn, V. Fimbres, E. Pollard, J. Mitchell, J. Ingram, R. Hellmers, D. Quig, and J. Hahn, “Significant association of urinary toxic metals and autism-related symptoms — A nonlinear statistical analysis with cross validation,” PLoS ONE, vol. 12, no. 1, e0169526, Jan. 2017. doi: 10.1371/journal.pone.0169526

  25. B. W. Bequette, F. Cameron, N. Baysal, D. Howsmon, B. Buckingham, D. Maahs, and C. Levy, “Algorithms for a single hormone closed-loop artificial pancreas: Challenges pertinent to chemical process operations and control,” Processes, vol. 4, no. 4, p. 39, Oct. 2016. doi: 10.3390/pr4040039

  26. D. P. Howsmon and J. Hahn, “Regularization techniques to overcome over-parameterization of complex biochemical reaction networks,” IEEE Life Sciences Letters, vol. 2, no. 3, pp. 31–34, Sep. 2016. doi: 10.1109/ LLS.2016.2646498

  27. D. Howsmon* , J. G. Zheng* , B. Zhang, J. Hahn, D. McGuinness, J. Hendler, and H. Ji, “Entity linking for biomedical literature,” BMC Medical Informatics and Decision Making, vol. 15, S4, Suppl 1 May 2015. doi: 10.1186/1472-6947-15-S1-S4

  28. D. Howsmon and B. W. Bequette, “Hypo- and hyperglycemic alarms: Devices and algorithms,” Journal of Diabetes Science and Technology, vol. 9, no. 5, pp. 1126–1137, Apr. 2015. doi: 10.1177/1932296815583507

  29. C. Klemashevich, C. Wu, D. Howsmon, R. C. Alaniz, K. Lee, and A. Jayaraman, “Rational identification of diet-derived postbiotics for improving intestinal microbiota function,” Current Opinion in Biotechnology, vol. 26, pp. 85–90, Apr. 2014. doi: 10.1016/j.copbio.2013.10.006