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Miniaturized implantable temperature sensors for the long-term monitoring of chronic intestinal inflammation

Nature Biomedical Engineering (2024)Cite this article

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Abstract

Diagnosing and monitoring inflammatory bowel diseases, such as Crohn’s disease, involves the use of endoscopic imaging, biopsies and serology. These infrequent tests cannot, however, identify sudden onsets and severe flare-ups to facilitate early intervention. Hence, about 70% of patients with Crohn’s disease require surgical intestinal resections in their lifetime. Here we report wireless, miniaturized and implantable temperature sensors for the real-time chronic monitoring of disease progression, which we tested for nearly 4 months in a mouse model of Crohn’s-disease-like ileitis. Local measurements of intestinal temperature via intraperitoneally implanted sensors held in place against abdominal muscular tissue via two sutures showed the development of ultradian rhythms at approximately 5 weeks before the visual emergence of inflammatory skip lesions. The ultradian rhythms showed correlations with variations in the concentrations of stress hormones and inflammatory cytokines in blood. Decreasing average temperatures over the span of approximately 23 weeks were accompanied by an increasing percentage of inflammatory species in ileal lesions. These miniaturized temperature sensors may aid the early treatment of inflammatory bowel diseases upon the detection of episodic flare-ups.

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Fig. 1: Implantable temperature sensors for monitoring Crohn’s-disease-like ileitis and their use in studies in mouse models.
Fig. 2: Ultradian rhythms in intestinal temperature for mice with spontaneous ileitis.
Fig. 3: Circadian disruptions in temperature for mice with spontaneous ileitis.
Fig. 4: Long-term trends in temperature and tissue inflammation.
Fig. 5: Circadian disruptions and influence of aging on PPARγ concentrations in ileal tissue.

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Data availability

The main data supporting the results in this study are available within the paper and its Supplementary Information. Source data for Figs. 2d, 3b and 4f, as well as representative individual histology images used to produce Figs. 4g and 5d, are available with this paper. A larger number of additional individual histology images used to produce Figs. 4g and 5d are available from the corresponding authors on reasonable request. Source data are provided with this paper.

Code availability

Data analysis (spline fits, FFT, wavelet transform, peak/valley analysis, moving standard deviation) made use of inbuilt functions in MATLAB. All parameters used for analysis are available in Methods.

References

  1. Jairath, V. & Feagan, B. G. Global burden of inflammatory bowel disease. Lancet Gastroenterol. Hepatol. 5, 2–3 (2020).

    Article  PubMed  Google Scholar 

  2. Kaplan, G. G. & Windsor, J. W. The four epidemiological stages in the global evolution of inflammatory bowel disease. Nat. Rev. Gastroenterol. Hepatol. 18, 56–66 (2021).

    Article  PubMed  Google Scholar 

  3. Kamm, M. A. Rapid changes in epidemiology of inflammatory bowel disease. Lancet 390, 2741–2742 (2017).

    Article  PubMed  Google Scholar 

  4. Khor, B., Gardet, A. & Xavier, R. J. Genetics and pathogenesis of inflammatory bowel disease. Nature 474, 307–317 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Torres, J., Mehandru, S., Colombel, J. F. & Peyrin-Biroulet, L. Crohn’s disease. Lancet 389, 1741–1755 (2017).

    Article  PubMed  Google Scholar 

  6. Santos, M. P. C., Gomes, C. & Torres, J. Familial and ethnic risk in inflammatory bowel disease. Ann. Gastroenterol. 31, 14–23 (2018).

    PubMed  Google Scholar 

  7. Goertz, R. S., Hensel, S., Wildner, D., Neurath, M. F. & Strobel, D. Bowel wall thickening and hyperemia assessed by high-frequency ultrasound indicate histological inflammation in Crohn’s ileitis. Abdom. Radiol. 46, 1855–1863 (2021).

    Article  Google Scholar 

  8. Brown, E. & Taylor, C. T. Hypoxia-sensitive pathways in intestinal inflammation. J. Physiol. 596, 2985–2989 (2018).

    Article  CAS  PubMed  Google Scholar 

  9. Li, J. et al. Dynamic role of macrophage CX3CR1 expression in inflammatory bowel disease. Immunol. Lett. 232, 39–44 (2021).

    Article  CAS  PubMed  Google Scholar 

  10. Cushing, K. & Higgins, P. D. R. Management of Crohn disease: a review. JAMA 325, 69–80 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Xiong, S. et al. Reverse translation approach generates a signature of penetrating fibrosis in Crohn’s disease that is associated with anti-TNF response. Gut 71, 1289–1301 (2022).

    Article  CAS  PubMed  Google Scholar 

  12. Hyun, J. G. et al. Anti-interferon-inducible chemokine, CXCL10, reduces colitis by impairing T helper-1 induction and recruitment in mice. Inflamm. Bowel Dis. 11, 799–805 (2005).

    Article  PubMed  Google Scholar 

  13. Burgmann, T. et al. The Manitoba Inflammatory Bowel Disease Cohort Study: prolonged symptoms before diagnosis—how much is irritable bowel syndrome? Clin. Gastroenterol. Hepatol. 4, 614–620 (2006).

    Article  PubMed  Google Scholar 

  14. Guglielmo, F. F. et al. Small bowel Crohn disease at CT and MR enterography: imaging atlas and glossary of terms. Radiographics 40, 354–375 (2020).

    Article  PubMed  Google Scholar 

  15. Calabrese, E., Zorzi, F. & Pallone, F. Ultrasound of the small bowel in Crohn’s disease. Int J. Inflamm. 2012, 964720 (2012).

    Google Scholar 

  16. Stenczel, N. D., Purcarea, M. R., Tribus, L. C. & Oniga, G. H. The role of the intestinal ultrasound in Crohn’s disease diagnosis and monitoring. J. Med. Life 14, 310–315 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  17. Yin, J. et al. The role of hypoxia-inducible factor 1-alpha in inflammatory bowel disease. Cell Biol. Int. 46, 46–51 (2022).

    Article  CAS  PubMed  Google Scholar 

  18. Pizarro, T. T. et al. SAMP1/YitFc mouse strain: a spontaneous model of Crohn’s disease-like ileitis. Inflamm. Bowel Dis. 17, 2566–2584 (2011).

    Article  PubMed  Google Scholar 

  19. Bury, M. I. et al. Self-assembling nanofibers inhibit inflammation in a murine model of Crohn’s-disease-like ileitis. Adv. Therap. 4, 2000274 (2021).

    Article  CAS  Google Scholar 

  20. Lucke, S. et al. Acute and chronic local inflammatory reaction after implantation of different extracellular porcine dermis collagen matrices in rats. BioMed. Res. Int. 2015, 938059 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  21. Schwerdt, H. N. et al. Long-term dopamine neurochemical monitoring in primates. Proc. Natl Acad. Sci. USA 114, 13260–13265 (2017).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  22. Chen, S. L. et al. The gut microbiota regulates acute foreign body reaction and tissue repair after biomaterial implantation. Biomaterials 289, 121807 (2022).

    Article  CAS  PubMed  Google Scholar 

  23. Ellison, G. W., Case, J. B. & Regier, P. J. Intestinal surgery in small animals: historical foundations, current thinking, and future horizons. Vet. Surg. 48, 1171–1180 (2019).

    Article  PubMed  Google Scholar 

  24. Doloff, J. C. et al. The surface topography of silicone breast implants mediates the foreign body response in mice, rabbits and humans. Nat. Biomed. Eng. 5, 1115–1130 (2021).

    Article  CAS  PubMed  Google Scholar 

  25. Park, G. et al. Immunologic and tissue biocompatibility of flexible/stretchable electronics and optoelectronics. Adv. Health. Mater. 3, 515–525 (2014).

    Article  CAS  Google Scholar 

  26. Matsuzaki, K. et al. In vivo demonstration of T lymphocyte migration and amelioration of ileitis in intestinal mucosa of SAMP1/Yit mice by the inhibition of MAdCAM-1. Clin. Exp. Immunol. 140, 22–31 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Lamont, E. W. & Amir, S. in Encyclopedia of Behavioral Neuroscience (eds Koob, G. F., Le Moal, M. & Thompson, R. F.) 257–261 (Academic Press, 2010).

  28. Goh, G. H., Maloney, S. K., Mark, P. J. & Blache, D. Episodic ultradian events—ultradian rhythms. Biology 8 doi, 10.3390/biology8010015 (2019).

  29. Smolensky, M. H., Hermida, R. C., Portaluppi, F., Haus, E. & Reinberg, A. in Hypertension 2nd edn (eds Oparil, S. & Weber, M.A.) 530–542 (W.B. Saunders, 2005).

  30. Arts, L. P. A. & van den Broek, E. L. The fast continuous wavelet transformation (fCWT) for real-time, high-quality, noise-resistant time-frequency analysis. Nat. Comput Sci. 2, 47–58 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Lou, H. & Ye, Z. [HRV signal analysis based on wavelet transform]. Sheng Wu Yi Xue Gong. Cheng Xue Za Zhi 23, 21–24 (2006).

    PubMed  Google Scholar 

  32. Addison, P. S. Wavelet transforms and the ECG: a review. Physiol. Meas. 26, R155–R199 (2005).

    Article  ADS  PubMed  Google Scholar 

  33. Rankin, G. B. Extraintestinal and systemic manifestations of inflammatory bowel disease. Med Clin. North Am. 74, 39–50 (1990).

    Article  CAS  PubMed  Google Scholar 

  34. Vavricka, S. R. et al. Extraintestinal manifestations of inflammatory bowel disease. Inflamm. Bowel Dis. 21, 1982–1992 (2015).

    Article  PubMed  Google Scholar 

  35. Gordon, C. J. The mouse thermoregulatory system: its impact on translating biomedical data to humans. Physiol. Behav. 179, 55–66 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Aschoff, J. Thermal conductance in mammals and birds—its dependence on body size and circadian phase. Comp. Biochem Phys. A 69, 611–619 (1981).

    Article  Google Scholar 

  37. Oh, S. et al. Simple, miniaturized biosensors for wireless mapping of thermoregulatory responses. Biosens. Bioelectron. 237, 115545 (2023).

    Article  CAS  PubMed  Google Scholar 

  38. Atreya, R. et al. Blockade of interleukin 6 trans signaling suppresses T-cell resistance against apoptosis in chronic intestinal inflammation: evidence in Crohn disease and experimental colitis in vivo. Nat. Med. 6, 583–588 (2000).

    Article  CAS  PubMed  Google Scholar 

  39. Atreya, R. et al. In vivo imaging using fluorescent antibodies to tumor necrosis factor predicts therapeutic response in Crohn’s disease. Nat. Med. 20, 313–318 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Langer, V. et al. IFN-gamma drives inflammatory bowel disease pathogenesis through VE-cadherin-directed vascular barrier disruption. J. Clin. Invest. 129, 4691–4707 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Bouma, G. & Strober, W. The immunological and genetic basis of inflammatory bowel disease. Nat. Rev. Immunol. 3, 521–533 (2003).

    Article  CAS  PubMed  Google Scholar 

  42. Mao, L., Kitani, A., Strober, W. & Fuss, I. J. The role of NLRP3 and IL-1beta in the pathogenesis of inflammatory bowel disease. Front. Immunol. 9, 2566 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  43. Liu, S., Russo, P. A., Baldassano, R. N. & Sullivan, K. E. CD68 expression is markedly different in Crohn’s disease and the colitis associated with chronic granulomatous disease. Inflamm. Bowel Dis. 15, 1213–1217 (2009).

    Article  PubMed  Google Scholar 

  44. Friedrich, M. et al. IL-1-driven stromal-neutrophil interactions define a subset of patients with inflammatory bowel disease that does not respond to therapies. Nat. Med. 27, 1970–1981 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Padmanabhan, P., Grosse, J., Asad, A. B., Radda, G. K. & Golay, X. Gastrointestinal transit measurements in mice with 99mTc-DTPA-labeled activated charcoal using NanoSPECT-CT. EJNMMI Res. 3, 60 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  46. Rahman, M. M., Afroz, S., Arthur, S. & Sundaram, U. Mast cell mediated regulation of small intestinal chloride malabsorption in SAMP1/YitFc mouse model of spontaneous chronic ileitis. Cells https://doi.org/10.3390/cells10030697 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  47. Gracie, D. J., Hamlin, P. J. & Ford, A. C. The influence of the brain–gut axis in inflammatory bowel disease and possible implications for treatment. Lancet Gastroenterol. Hepatol. 4, 632–642 (2019).

    Article  PubMed  Google Scholar 

  48. Carabotti, M., Scirocco, A., Maselli, M. A. & Severi, C. The gut–brain axis: interactions between enteric microbiota, central and enteric nervous systems. Ann. Gastroenterol. 28, 203–209 (2015).

    PubMed  PubMed Central  Google Scholar 

  49. Farhadi, A. et al. Heightened responses to stressors in patients with inflammatory bowel disease. Am. J. Gastroenterol. 100, 1796–1804 (2005).

    Article  PubMed  Google Scholar 

  50. Vidrich, A. et al. Altered epithelial cell lineage allocation and global expansion of the crypt epithelial stem cell population are associated with ileitis in SAMP1/YitFc mice. Am. J. Pathol. 166, 1055–1067 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Rivera-Nieves, J. et al. Emergence of perianal fistulizing disease in the SAMP1/YitFc mouse, a spontaneous model of chronic ileitis. Gastroenterology 124, 972–982 (2003).

    Article  PubMed  Google Scholar 

  52. Daynes, R. A. & Jones, D. C. Emerging roles of PPARs in inflammation and immunity. Nat. Rev. Immunol. 2, 748–759 (2002).

    Article  CAS  PubMed  Google Scholar 

  53. Wang, N. et al. Vascular PPARgamma controls circadian variation in blood pressure and heart rate through Bmal1. Cell Metab. 8, 482–491 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Berger, J. P., Akiyama, T. E. & Meinke, P. T. PPARs: therapeutic targets for metabolic disease. Trends Pharmacol. Sci. 26, 244–251 (2005).

    Article  CAS  PubMed  Google Scholar 

  55. Evans, R. M., Barish, G. D. & Wang, Y. X. PPARs and the complex journey to obesity. Nat. Med. 10, 355–361 (2004).

    Article  CAS  PubMed  Google Scholar 

  56. Sugawara, K. et al. Linkage to peroxisome proliferator-activated receptor-gamma in SAMP1/YitFc mice and in human Crohn’s disease. Gastroenterology 128, 351–360 (2005).

    Article  CAS  PubMed  Google Scholar 

  57. Baumgart, D. C. & Sandborn, W. J. Crohn’s disease. Lancet 380, 1590–1605 (2012).

    Article  PubMed  Google Scholar 

  58. Favazzo, L. J. et al. The gut microbiome-joint connection: implications in osteoarthritis. Curr. Opin. Rheumatol. 32, 92–101 (2020).

    Article  PubMed  Google Scholar 

  59. Arora, V. et al. Gut-microbiota modulation: the impact of the gut-microbiota on osteoarthritis. Gene 785, 145619 (2021).

    Article  CAS  PubMed  Google Scholar 

  60. Sharma, S. et al. Location-aware ingestible microdevices for wireless monitoring of gastrointestinal dynamics. Nat. Electron. 6, 242–256 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  61. Tu, J. B. et al. A wireless patch for the monitoring of C-reactive protein in sweat. Nat. Biomed. Eng. https://doi.org/10.1038/s41551-023-01059-5 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  62. Wagatsuma, K., Yokoyama, Y. & Nakase, H. Role of biomarkers in the diagnosis and treatment of inflammatory bowel disease. Life https://doi.org/10.3390/life11121375 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  63. Chen, P. et al. Serum biomarkers for inflammatory bowel disease. Front. Med. 7, 123 (2020).

    Article  ADS  Google Scholar 

  64. Winogrodzki, T. et al. TNF DeltaARE pigs: a translational Crohn’s disease model. J. Crohns Colitis 17, 1128–1138 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  65. Wanner, S. P., Costa, K. A., Soares, A. D., Cardoso, V. N. & Coimbra, C. C. Physical exercise-induced changes in the core body temperature of mice depend more on ambient temperature than on exercise protocol or intensity. Int. J. Biometeorol. 58, 1077–1085 (2014).

    Article  ADS  PubMed  Google Scholar 

  66. Madhvapathy, S. R. et al. Implantable bioelectronic systems for early detection of kidney transplant rejection. Science 381, 1105–1112 (2023).

    Article  ADS  CAS  PubMed  Google Scholar 

  67. Zhang, L. N. et al. Physiological and behavioral responses to intermittent starvation in C57BL/6J mice. Physiol. Behav. 105, 376–387 (2012).

    Article  CAS  PubMed  Google Scholar 

  68. Severinsen, T. & Munch, I. C. Body core temperature during food restriction in rats. Acta Physiol. Scand. 165, 299–305 (1999).

    Article  CAS  PubMed  Google Scholar 

  69. Kararli, T. T. Comparison of the gastrointestinal anatomy, physiology, and biochemistry of humans and commonly used laboratory animals. Biopharm. Drug Dispos. 16, 351–380 (1995).

    Article  CAS  PubMed  Google Scholar 

  70. Casteleyn, C., Rekecki, A., Van der Aa, A., Simoens, P. & Van den Broeck, W. Surface area assessment of the murine intestinal tract as a prerequisite for oral dose translation from mouse to man. Lab. Anim./ 44, 176–183 (2010).

    Article  CAS  PubMed  Google Scholar 

  71. Yang, Q. et al. Photocurable bioresorbable adhesives as functional interfaces between flexible bioelectronic devices and soft biological tissues. Nat. Mater. 20, 1559–1570 (2021).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  72. Hwang, S. W. et al. A physically transient form of silicon electronics. Science 337, 1640–1644 (2012).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  73. Shih, T. C., Yuan, P., Lin, W. L. & Kou, H. S. Analytical analysis of the Pennes bioheat transfer equation with sinusoidal heat flux condition on skin surface. Med. Eng. Phys. 29, 946–953 (2007).

    Article  PubMed  Google Scholar 

  74. Yang, Y. et al. Wireless multilateral devices for optogenetic studies of individual and social behaviors. Nat. Neurosci. 24, 1035–1045 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Castellani, M. P., Rioux, T. P., Castellani, J. W., Potter, A. W. & Xu, X. A geometrically accurate 3 dimensional model of human thermoregulation for transient cold and hot environments. Comput. Biol. Med. 138, 104892 (2021).

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

We thank F. Turek, M. Hotz-Vitaterna and K. Summa for useful discussions; M. Seniw (Simpson Querrey Institute, Northwestern University) for the illustrations in Fig. 1c; and H. M. Arafa, D. Ostojich and J.T. Williams for preliminary efforts in microfabrication and near-field communication device prototypes. This work made use of the MatCI Facility supported by the Materials Research Science and Engineering Center (MRSEC) program of the National Science Foundation (NSF) (DMR-1720139) at the Materials Research Center of Northwestern University, and of the micro/nano-fabrication (NUFAB) facility of Northwestern University’s Atomic and Nanoscale Characterization Experimental Center, which has received support from the SHyNE Resource (NSF ECCS-2025633), the International Institute for Nanotechnology and Northwestern’s MRSEC program. S.R.M and J.L.C. disclose support for the research described in this study from the NSF Graduate Research Fellowship Program (NSF DGE-2234667). The work was supported by the Querrey–Simpson Institute for Bioelectronics.

Author information

Author notes

  1. These authors contributed equally: Surabhi R. Madhvapathy, Matthew I. Bury.

Authors and Affiliations

  1. Department of Materials Science and Engineering, Northwestern University, Evanston, IL, USA

    Surabhi R. Madhvapathy, Joanna L. Ciatti & John A. Rogers

  2. Querrey Simpson Institute for Bioelectronics, Northwestern University, Evanston, IL, USA

    Surabhi R. Madhvapathy, Joanna L. Ciatti & John A. Rogers

  3. Division of Pediatric Urology, Department of Surgery, Ann & Robert H. Lurie Children’s Hospital of Chicago, Chicago, IL, USA

    Matthew I. Bury & Arun K. Sharma

  4. Stanley Manne Children’s Research Institute, Louis A. Simpson and Kimberly K. Querrey Biomedical Research Center, Chicago, IL, USA

    Matthew I. Bury & Arun K. Sharma

  5. Department of Urology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA

    Larry W. Wang & Arun K. Sharma

  6. Department of Mechanical Engineering, Rice University, Houston, TX, USA

    Raudel Avila

  7. Department of Mechanical Engineering, Northwestern University, Evanston, IL, USA

    Yonggang Huang

  8. Department of Civil Engineering, Northwestern University, Evanston, IL, USA

    Yonggang Huang

  9. Simpson Querrey Institute, Northwestern University, Chicago, IL, USA

    Arun K. Sharma

  10. Department of Biomedical Engineering, Northwestern University, Evanston, IL, USA

    Arun K. Sharma & John A. Rogers

  11. Department of Neurological Surgery, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA

    John A. Rogers

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Contributions

S.R.M., M.I.B., A.K.S. and J.A.R. conceived the project. S.R.M. designed the device hardware, software and encapsulation; fabricated devices; calibrated devices; conducted video analysis; and performed benchtop testing/characterization (with assistance from J.L.C.) and temperature data analysis. M.I.B. designed the surgical procedure and conducted surgeries, post-operative animal monitoring/care (with assistance from L.W.W.), motility measurements, histology sample preparation (with assistance from L.W.W.), analysis of quantitative histology (with assistance from L.W.W.), radiograph collection, video collection and blood collection/analysis. R.A. and Y.H. helped with thermal, electromagnetic and mechanical-modelling efforts associated with device operation. S.R.M. and M.I.B. performed data visualization. S.R.M., M.I.B., A.K.S. and J.A.R. analysed the data. S.R.M., M.I.B., A.K.S. and J.A.R. wrote the paper. All authors read and provided comments on the paper. J.A.R. and A.K.S. jointly supervised the work.

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Correspondence to Arun K. Sharma or John A. Rogers.

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Competing interests

J.A.R., A.K.S., S.R.M., and M.I.B. are co-inventors on a patent related to the technology (US Patent App. 63/604,400) described in this work. The other authors declare no competing interests.

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Nature Biomedical Engineering thanks Jonathan Cooper, Wei Gao and Taeyoon Lee for their contribution to the peer review of this work. Peer reviewer reports are available.

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Extended data

Extended Data Fig. 1 FEA modeling of the temperature sensitivity of the device to temperature fluctuations in the intestines.

(a) Temperature profile in the sensor over a 5-hour period to reach steady state temperature when the temperature of the intestines increases by 1 °C (black), remains the same 0 °C (red), and decreases by 1 °C (blue) with respect to the body temperature. The core body temperature was fixed at 37 °C. (b) Steady state temperature change (ΔT = Tintestines – Tcore) profile between the surface of the intestines and the outer skin layer in a mouse for the three cases in (a); the distance between the intestines and skin is assumed to be 5 mm and the thickness of the skin layer is 1 mm. (c) FEA model for (a,b). (d) Sinusoidal temperature profile at the surface of the intestines over a 24-hr period and the corresponding temperature profile in the temperature sensors showing excellent agreement by capturing the thermal fluctuations. (e) A 4th order polynomial temperature profile at the surface of the ‘lesion’ intestines over a 24-hr period and the corresponding temperature profile in the temperature sensors showing excellent agreement by capturing the thermal fluctuations. In both (d,e), the distance between the sensor and intestines is 0.75 mm. (f) (Top) Temperature profile in the sensor as the vertical separation distance between the surface of the intestines and sensor increases from 5 mm to 100 mm, modeling the scenario in a human. The temperature in the intestines is modeled as a sinusoidal wave. As the vertical separation distance increases to 50 mm and 100 mm the sensor is unable to pick up the thermal fluctuations in the intestines. (Bottom) Schematic of the FEA model. (g) Temperature profiles in the sensor as a function of time when the vertical distance between the sensor increases from 0.75 mm to 3.75 mm showing that for all cases the sensor can capture the 4th order polynomial profile of the intestines. (h) Temperature profiles in the sensor as a function of time when the horizontal distance, or lateral misalignment, between the sensor increases from 5 mm to 30 mm. For the cases when the sensor is 20 mm and 30 mm away from the edge of the intestines the sensor is unable to capture the thermal fluctuations at the surface of the intestines. (i) (Top) Thermal profiles for the sensor when placed on top of the lesion region (solid red), normal region (solid blue), and between lesion and normal region (solid black). The thermal profiles are a sinusoidal wave for the normal intestine (dashed blue) and 4th order polynomial for the lesion intestine (dashed red). (Bottom) Schematic of the arrangement for the lesion intestines, normal intestines, and the sensor placement. (j) (Top) Steady state temperature limits at the sensor when the intestine is empty (dashed blue) and with fecal matter (dashed red). The black curve shows the thermal profile when fecal matter enters (temperature increases) and leaves (temperature decreases) the intestine over a period of 8 hrs. (Bottom) Schematic of the model showing the difference between the internal part of the intestine for the empty/fecal cases. (k) Surface plot of the steady state temperature in the sensor based on a parametric sweep of the distance between the sensor and intestine (horizontal axis) and the thermal conductivity of the intestines (vertical axis). (l) Transient heat transfer process over a 12-hr process to reach thermal equilibrium in the intestine’s region.

Extended Data Fig. 2 A DSS-induced model of colitis.

Tintestines as a function of time for individual AKR/J mice subject to intermittent administration of (a, b) 1% and (c, d) 3% by volume DSS in the drinking water over 107–110 days. The red shaded regions indicate the time period for which DSS was administered. Animals were killed on day 107 in panels (b, c) and day 110 in panels (a, d). (e, f) Tintestines as a function of time for individual mice subject to 5% by volume of DSS in the drinking water. The red shaded region indicates the time window for which DSS was administered. Animals were euthanized on day 35. The black arrows in all panels indicate a significant drop in Tintestines after administration of DSS, if applicable.

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Madhvapathy, S.R., Bury, M.I., Wang, L.W. et al. Miniaturized implantable temperature sensors for the long-term monitoring of chronic intestinal inflammation. Nat. Biomed. Eng (2024). https://doi.org/10.1038/s41551-024-01183-w

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