Age-Related In Vivo Structural Changes in the Male Mouse Olfactory Bulb and Their Correlation with Olfactory-Driven Behavior
Abstract
:Simple Summary
Abstract
1. Introduction
2. Materials and Methods
2.1. Animals
2.2. Behavioral Tests
2.2.1. Cord Test
2.2.2. Open-Field Test
2.2.3. Swim Test
2.2.4. Light Avoidance
2.2.5. Olfactory Test 1: Food Finding
2.2.6. Olfactory Test 2: Olfactory Preference Test
2.2.7. Pole Test
2.2.8. Intraspecific Intruder Test
2.2.9. Predation Test
2.3. Magnetic Resonance Imaging
2.3.1. Cerebral Blood Volume
2.3.2. Diffusion Tensor Imaging
2.3.3. OB Volume
2.4. Statistical Analysis
3. Results
3.1. MRI
3.2. Behavioral Tests
3.2.1. Motor Performance
3.2.2. Olfactory Function
3.2.3. Cognitive Performance
3.2.4. Emotional Reactivity
3.2.5. Correlation Analysis of MRI and Behavioral Variables
4. Discussion
4.1. MRI Variables in the Two Age Groups
4.2. Behavioral Differences between Young and Elderly Mice
4.2.1. Motor Performance
4.2.2. Olfactory Function
4.2.3. Cognitive Performance
4.2.4. Emotional Reactivity
4.2.5. Correlative Analysis of RF-Selected MRI and Behavioral Variables
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Buschhüter, D.; Smitka, M.; Puschmann, S.; Gerber, J.; Witt, M.; Abolmaali, N.; Hummel, T. Correlation between olfactory bulb volume and olfactory function. Neuroimage 2008, 42, 498–502. [Google Scholar] [CrossRef] [PubMed]
- Mobley, A.S.; Rodriguez-Gil, D.J.; Imamura, F.; Greer, C.A. Aging in the olfactory system. Trends Neurosci. 2014, 37, 77–84. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Sorokowska, A.; Schriever, V.A.; Gudziol, V.; Hummel, C.; Hähner, A.; Iannilli, E.; Sinding, C.; Aziz, M.; Seo, H.S.; Negoias, S.; et al. Changes of olfactory abilities in relation to age: Odor identification in more than 1400 people aged 4 to 80 years. Eur. Arch. Oto-Rhino-Laryngol. 2015, 272, 1937–1944. [Google Scholar] [CrossRef] [Green Version]
- Kondo, K.; Kikuta, S.; Ueha, R.; Suzukawa, K.; Yamasoba, T. Age-Related Olfactory Dysfunction: Epidemiology, Pathophysiology, and Clinical Management. Front. Aging Neurosci. 2020, 12, 208. [Google Scholar] [CrossRef] [PubMed]
- Doty, R.L.; Shaman, P.; Applebaum, S.L.; Giberson, R.; Siksorski, L.; Rosenberg, L. Smell Identification Ability: Changes with Age. Science 1984, 226, 1441–1443. [Google Scholar] [CrossRef] [PubMed]
- Mandairon, N.; Linster, C. Odor Perception and Olfactory Bulb Plasticity in Adult Mammals. J. Neurophysiol. 2009, 101, 2204–2209. [Google Scholar] [CrossRef] [Green Version]
- Pignatelli, A.; Belluzzi, O. Neurogenesis in the Adult Olfactory Bulb. In The Neurobiology of Olfaction; Chapter 11; Menini, A., Ed.; CRC Press/Taylor & Francis: Boca Raton, FL, USA, 2010. [Google Scholar]
- Sakamoto, M.; Ieki, N.; Miyoshi, G.; Mochimaru, D.; Miyachi, H.; Imura, T.; Yamaguchi, M.; Fishell, G.; Mori, K.; Kageyama, R.; et al. Continuous Postnatal Neurogenesis Contributes to Formation of the Olfactory Bulb Neural Circuits and Flexible Olfactory Associative Learning. J. Neurosci. 2014, 34, 5788–5799. [Google Scholar] [CrossRef] [Green Version]
- Fitzek, M.; Patel, P.K.; Solomon, P.D.; Lin, B.; Hummel, T.; Schwob, J.E.; Holbrook, E.H. Integrated age-related immunohistological changes occur in human olfactory epithelium and olfactory bulb. J. Comp. Neurol. 2022, 530, 2154–2175. [Google Scholar] [CrossRef]
- Ache, B.W.; Young, J.M. Olfaction: Diverse Species, Conserved Principles. Neuron 2005, 48, 417–430. [Google Scholar] [CrossRef] [Green Version]
- Hinds, J.W.; McNelly, N.A. Aging in the rat olfactory bulb: Quantitative changes in mitral cell organelles and somato-dendritic synapses. J. Comp. Neurol. 1979, 184, 811–819. [Google Scholar] [CrossRef]
- Curcio, C.A.; McNelly, N.A.; Hinds, J.W. Aging in the rat olfactory system: Relative stability of piriform cortex contrasts with changes in olfactory bulb and olfactory epithelium. J. Comp. Neurol. 1985, 235, 519–528. [Google Scholar] [CrossRef] [PubMed]
- Baker, H.; Franzen, L.; Stone, D.; Cho, J.Y.; Margolis, F.L. Expression of tyrosine hydroxylase in the aging, rodent olfactory system. Neurobiol. Aging 1995, 16, 119–128. [Google Scholar] [CrossRef] [PubMed]
- Morterá, P.; Herculano-Houzel, S. Age-related neuronal loss in the rat brain starts at the end of adolescence. Front. Neuroanat. 2012, 6, 45. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Cross, D.J.; Flexman, J.A.; Anzai, Y.; Maravilla, K.R.; Minoshima, S. Age-related decrease in axonal transport measured by MR imaging in vivo. Neuroimage 2008, 39, 915–926. [Google Scholar] [CrossRef]
- Fu, Y.; Yu, Y.; Paxinos, G.; Watson, C.; Rusznák, Z. Aging-dependent changes in the cellular composition of the mouse brain and spinal cord. Neuroscience 2015, 290, 406–420. [Google Scholar] [CrossRef]
- Richard, M.B.; Taylor, S.R.; Greer, C.A. Age-induced disruption of selective olfactory bulb synaptic circuits. Proc. Natl. Acad. Sci. USA 2010, 107, 15613–15618. [Google Scholar] [CrossRef] [Green Version]
- Hinds, J.W.; McNelly, N.A. Aging of the rat olfactory bulb: Growth and atrophy of constituent layers and changes in size and number of mitral cells. J. Comp. Neurol. 1977, 171, 345–367. [Google Scholar] [CrossRef]
- Mirich, J.M.; Williams, N.C.; Berlau, D.; Brunjes, P.C. Comparative study of aging in the mouse olfactory bulb. J. Comp. Neurol. 2002, 454, 361–372. [Google Scholar] [CrossRef]
- Forbes, W.B. Aging-related morphological changes in the main olfactory bulb of the fischer 344 rat. Neurobiol. Aging 1984, 5, 93–99. [Google Scholar] [CrossRef]
- Oettl, L.-L.; Kelsch, W. Oxytocin and Olfaction. Curr. Top. Behav. Neurosci. 2018, 35, 55–75. [Google Scholar] [CrossRef]
- Boesveldt, S.; Parma, V. The importance of the olfactory system in human well-being, through nutrition and social behavior. Cell Tissue Res. 2021, 383, 559–567. [Google Scholar] [CrossRef] [PubMed]
- Ishii, K.; Touhara, K. Neural circuits regulating sexual behaviors via the olfactory system in mice. Neurosci. Res. 2019, 140, 59–76. [Google Scholar] [CrossRef] [PubMed]
- Mucignat-Caretta, C. Processing of intraspecific chemical signals in the rodent brain. Cell Tissue Res. 2021, 383, 525–533. [Google Scholar] [CrossRef] [PubMed]
- Hwang, B.Y.; Mampre, D.; Penn, R.; Anderson, W.S.; Kang, J.; Kamath, V. Olfactory Testing in Temporal Lobe Epilepsy: A Systematic Review. Curr. Neurol. Neurosci. Rep. 2020, 20, 65. [Google Scholar] [CrossRef]
- Xu, M.; Minagawa, Y.; Kumazaki, H.; Okada, K.-I.; Naoi, N. Prefrontal Responses to Odors in Individuals with Autism Spectrum Disorders: Functional NIRS Measurement Combined with a Fragrance Pulse Ejection System. Front. Hum. Neurosci. 2020, 14, 523456. [Google Scholar] [CrossRef]
- Simonet, C.; Schrag, A.; Lees, A.J.; Noyce, A.J. The motor prodromes of parkinson’s disease: From bedside observation to large-scale application. J. Neurol. 2019, 268, 2099–2108. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Doty, R.L.; Hawkes, C.H. Chemosensory dysfunction in neurodegenerative diseases. Handb. Clin. Neurol. 2019, 164, 325–360. [Google Scholar] [CrossRef]
- Devanand, D. Olfactory Identification Deficits, Cognitive Decline, and Dementia in Older Adults. Am. J. Geriatr. Psychiatry 2016, 24, 1151–1157. [Google Scholar] [CrossRef] [Green Version]
- Suzuki, H.; Teranishi, M.; Katayama, N.; Nakashima, T.; Sugiura, S.; Sone, M. Relationship between cognitive impairment and olfactory function among older adults with olfactory impairment. Auris Nasus Larynx 2020, 48, 420–427. [Google Scholar] [CrossRef]
- Klein, M.; Lohr, C.; Droste, D. Age-Dependent Heterogeneity of Murine Olfactory Bulb Astrocytes. Front. Aging Neurosci. 2020, 12, 172. [Google Scholar] [CrossRef]
- Vaz, R.P.; Pereira, P.A.; Madeira, M.D. Age effects on the nucleus of the lateral olfactory tract of the rat. J. Comp. Neurol. 2016, 524, 759–771. [Google Scholar] [CrossRef] [PubMed]
- Lomidze, N.; Zhvania, M.G.; Tizabi, Y.; Japaridze, N.; Pochkhidze, N.; Rzayev, F.; Gasimov, E. Age-related behavioral and ultrastructural changes in the rat amygdala. Dev. Neurobiol. 2020, 80, 433–442. [Google Scholar] [CrossRef]
- Wang, J.; Eslinger, P.J.; Smith, M.B.; Yang, Q.X. Functional Magnetic Resonance Imaging Study of Human Olfaction and Normal Aging. J. Gerontol. A Biol. Sci. Med. Sci. 2005, 60, 510–514. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Pautler, R.G.; Koretsky, A.P. Tracing Odor-Induced Activation in the Olfactory Bulbs of Mice Using Manganese-Enhanced Magnetic Resonance Imaging. Neuroimage 2002, 16, 441–448. [Google Scholar] [CrossRef] [PubMed]
- Schafer, J.R.; Kida, I.; Rothman, D.L.; Hyder, F.; Xu, F. Adaptation in the rodent olfactory bulb measured by fMRI. Magn. Reson. Med. 2005, 54, 443–448. [Google Scholar] [CrossRef] [PubMed]
- Martin, C.; Grenier, D.; Thévenet, M.; Vigouroux, M.; Bertrand, B.; Janier, M.; Ravel, N.; Litaudon, P. fMRI visualization of transient activations in the rat olfactory bulb using short odor stimulations. Neuroimage 2007, 36, 1288–1293. [Google Scholar] [CrossRef] [Green Version]
- Xu, F.; Schaefer, M.; Kida, I.; Schafer, J.; Liu, N.; Rothman, D.L.; Hyder, F.; Restrepo, D.; Shepherd, G.M. Simultaneous activation of mouse main and accessory olfactory bulbs by odors or pheromones. J. Comp. Neurol. 2005, 489, 491–500. [Google Scholar] [CrossRef]
- Watanabe, T.; Frahm, J.; Michaelis, T. Functional mapping of neural pathways in rodent brainin vivo using manganese-enhanced three-dimensional magnetic resonance imaging. NMR Biomed. 2004, 17, 554–568. [Google Scholar] [CrossRef]
- Boretius, S.; Kasper, L.; Tammer, R.; Michaelis, T.; Frahm, J. MRI of cellular layers in mouse brain in vivo. Neuroimage 2009, 47, 1252–1260. [Google Scholar] [CrossRef]
- Chuang, K.-H.; Belluscio, L.; Koretsky, A.P. In vivo detection of individual glomeruli in the rodent olfactory bulb using manganese enhanced MRI. Neuroimage 2010, 49, 1350–1356. [Google Scholar] [CrossRef] [Green Version]
- Massimino, M.L.; Redaelli, M.; Bertoli, A.; Sorgato, M.C.; Mucignat-Caretta, C. Altered behavioral aspects of aged mice lacking the cellular prion protein. Physiol. Behav. 2013, 119, 86–91. [Google Scholar] [CrossRef] [PubMed]
- Bontempi, P.; Cisterna, B.; Malatesta, M.; Nicolato, E.; Mucignat-Caretta, C.; Zancanaro, C. A smaller olfactory bulb in a mouse model of Down syndrome. Acta Neurobiol. Exp. Wars 2020, 80, 375–380. [Google Scholar] [CrossRef] [PubMed]
- Bontempi, P.; Busato, A.; Bonafede, R.; Schiaffino, L.; Scambi, I.; Sbarbati, A.; Mariotti, R.; Marzola, P. MRI reveals therapeutical efficacy of stem cells: An experimental study on the SOD1(G93A) animal model. Magn. Reson. Med. 2018, 79, 459–469. [Google Scholar] [CrossRef] [PubMed]
- Mariotti, R.; Fattoretti, P.; Malatesta, M.; Nicolato, E.; Sandri, M.; Zancanaro, C. Forced mild physical training improves blood volume in the motor and hippocampal cortex of old mice. J. Nutr. Health Aging 2014, 18, 178–183. [Google Scholar] [CrossRef]
- Basser, P.; Mattiello, J.; LeBihan, D. MR diffusion tensor spectroscopy and imaging. Biophys. J. 1994, 66, 259–267. [Google Scholar] [CrossRef] [Green Version]
- Le Bihan, D.; Poupon, C.; Clark, C.A.; Pappata, S.; Molko, N.; Chabriat, H. Diffusion tensor imaging: Concepts and applications. J. Magn. Reson. Imaging 2001, 13, 534–546. [Google Scholar] [CrossRef]
- Alexander, A.L.; Lee, J.E.; Lazar, M.; Field, A.S. Diffusion tensor imaging of the brain. Neurotherapeutics 2007, 4, 316–329. [Google Scholar] [CrossRef] [Green Version]
- Hopkins, W.G. Internet Society for Sports Science. A Scale of Magnitude for Effect Statistics. 2016. Available online: http://www.sportsci.org/resource/stats/index.html (accessed on 25 November 2022).
- Breiman, L. Random forests. Mach. Learn. 2001, 45, 5–32. [Google Scholar] [CrossRef] [Green Version]
- Ishwaran, H.; Lu, M. Standard errors and confidence intervals for variable importance in random forest regression, classification, and survival. Stat. Med. 2019, 38, 558–582. [Google Scholar] [CrossRef]
- Eis, M.; Els, T.; Hoehn-Berlage, M. High resolution quantitative relaxation and diffusion MRI of three different experimental brain tumors in rat. Magn. Reson. Med. 1995, 34, 835–844. [Google Scholar] [CrossRef]
- Cohen-Adad, J. What can we learn from T2* maps of the cortex? Neuroimage 2014, 93 Pt 2, 189–200. [Google Scholar] [CrossRef]
- Knight, M.J.; McCann, B.; Tsivos, D.; Dillon, S.; Coulthard, E.; Kauppinen, R.A. Quantitative T2 mapping of white matter: Applications for ageing and cognitive decline. Phys. Med. Biol. 2016, 61, 5587–5605. [Google Scholar] [CrossRef]
- Sampaio-Baptista, C.; Khrapitchev, A.A.; Foxley, S.; Schlagheck, T.; Scholz, J.; Jbabdi, S.; DeLuca, G.C.; Miller, K.L.; Taylor, A.; Thomas, N.; et al. Motor Skill Learning Induces Changes in White Matter Microstructure and Myelination. J. Neurosci. 2013, 33, 19499–19503. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Tuch, D.S.; Salat, D.H.; Wisco, J.J.; Zaleta, A.K.; Hevelone, N.D.; Rosas, H.D. Choice reaction time performance correlates with diffusion anisotropy in white matter pathways supporting visuospatial attention. Proc. Natl. Acad. Sci. USA 2005, 102, 12212–12217. [Google Scholar] [CrossRef] [Green Version]
- Friedrich, P.; Fraenz, C.; Schlüter, C.; Ocklenburg, S.; Mädler, B.; Güntürkün, O.; Genç, E. The Relationship Between Axon Density, Myelination, and Fractional Anisotropy in the Human Corpus Callosum. Cereb. Cortex 2020, 30, 2042–2056. [Google Scholar] [CrossRef] [PubMed]
- Zhang, J.; van Zijl, P.C.; Mori, S. Three-Dimensional Diffusion Tensor Magnetic Resonance Microimaging of Adult Mouse Brain and Hippocampus. Neuroimage 2002, 15, 892–901. [Google Scholar] [CrossRef] [PubMed]
- Helpern, J.A.; Lee, S.-P.; Falangola, M.F.; Dyakin, V.V.; Bogart, A.; Ardekani, B.; Duff, K.; Branch, C.; Wisniewski, T.; de Leon, M.J.; et al. MRI assessment of neuropathology in a transgenic mouse model of Alzheimer’s disease. Magn. Reson. Med. 2004, 51, 794–798. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Ballak, S.B.; Degens, H.; de Haan, A.; Jaspers, R.T. Aging related changes in determinants of muscle force generating capacity: A comparison of muscle aging in men and male rodents. Ageing Res. Rev. 2014, 14, 43–55. [Google Scholar] [CrossRef]
- Russart, K.L.; Nelson, R.J. Artificial light at night alters behavior in laboratory and wild animals. J. Exp. Zool. A Ecol. Integr. Physiol. 2018, 329, 401–408. [Google Scholar] [CrossRef] [Green Version]
- Vuralli, D.; Wattiez, A.-S.; Russo, A.F.; Bolay, H. Behavioral and cognitive animal models in headache research. J. Headache Pain 2019, 20, 11. [Google Scholar] [CrossRef] [Green Version]
- Blanchard, D.C. Are cognitive aspects of defense a core feature of anxiety and depression? Neurosci. Biobehav. Rev. 2022, 144, 104947. [Google Scholar] [CrossRef] [PubMed]
- Mucignat-Caretta, C.; Bondi’, M.; Caretta, A. Animal models of depression: Olfactory lesions affect amygdala, subventricular zone, and aggression. Neurobiol. Dis. 2004, 16, 386–395. [Google Scholar] [CrossRef]
- Mucignat-Caretta, C.; Cavaggioni, A.; Redaelli, M.; Da Dalt, L.; Zagotto, G.; Gabai, G. Age and isolation influence steroids release and chemical signaling in male mice. Steroids 2014, 83, 10–16. [Google Scholar] [CrossRef]
- Mucignat-Caretta, C.; Caretta, A. Urinary chemical cues affect light-avoidance behaviour in male laboratory mice, Mus musculus. Anim. Behav. 1999, 57, 765–769. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Mucignat-Caretta, C.; Caretta, A. Chemical signals in male house mice urine: Protein-bound molecules modulate interaction between sexes. Behaviour 1999, 136, 331–343. [Google Scholar] [CrossRef]
- Bolognin, S.; Pasqualetto, F.; Mucignat-Caretta, C.; Ščančar, J.; Milačič, R.; Zambenedetti, P.; Cozzi, B.; Zatta, P. Effects of a Copper-Deficient Diet on the Biochemistry, Neural Morphology and Behavior of Aged Mice. PLoS ONE 2012, 7, e47063. [Google Scholar] [CrossRef] [PubMed]
- Oizumi, H.; Kuriyama, N.; Imamura, S.; Tabuchi, M.; Omiya, Y.; Mizoguchi, K.; Kobayashi, H. Influence of aging on the behavioral phenotypes of C57BL/6J mice after social defeat. PLoS ONE 2019, 14, e0222076. [Google Scholar] [CrossRef] [Green Version]
Variable | Young (n = 22) | Elderly (n = 19) | Z | p-Value |
---|---|---|---|---|
Bulb volume (mm3) | 26.0 (4.0) | 25.0 (5.0) | −0.464 | 0.643 |
T2 maps (ms) | 61.56 (1.80) | 57.94 (1.15) | −4.301 | <0.001 |
rCBV | 0.529 (0.15) | 0.555 (0.11) | −1.070 | 0.285 |
FA | 0.2764 (0.03) | 0.3090 (0.07) | −2.902 | 0.004 |
ADC (×10−3) (mm2/s) | 0.63 (0.02) | 0.65 (0.03) | −0.397 | 0.705 |
AD (×10−3) (mm2/s) | 0.83 (0.04) | 0.88 (0.01) | −1.098 | 0.272 |
RD (×10−3) (mm2/s) | 0.54 (0.02) | 0.54 (0.06) | −0.837 | 0.404 |
Test | Variable | Young (n = 23) | Elderly (n = 21) | Z | p-Value |
---|---|---|---|---|---|
Food finding | Invisible (s) | 38.0 (20.0) | 37.0 (64.0) | −0.082 | 0.934 |
Visible (s) | 21.0 (19.0) | 12.0 (30.0) | −1.294 | 0.196 | |
Intraspecific intruder | Latency 1° attempt (s) | 267.0 (249.0) | 253.0 (803.0) | −0.590 | 0.555 |
Predation | Latency 1° attempt (s) | 1800.0 (1278.0) | 1800.0 (239.0) | −2.323 | 0.020 |
Swim | Distance (cm) | 1897.0 (522.0) | 2077.0 (410.5) | −2.691 | 0.007 |
Resting time (s) | 26.0 (18.0) | 31.0 (29.0) | −0.717 | 0.473 | |
Pole day 1 | Time to descend (s) | 34.0 (16.0) | 50.0 (55.25) | −1.487 | 0.137 |
Pole day 2 | Time to descend (s) | 14.0 (14.0) | 14.0 (11.75) | −0.011 | 0.991 |
Pole day 3 | Time to descend (s) | 9.0 (4.0) | 9.0 (5.0) | −0.778 | 0.437 |
Pole day 4 | Time to descend (s) | 6.0 (4.0) | 9.0 (3.25) | −3.019 | 0.003 |
Cord | Time to fall (s) | 8.0 (10.0) | 4.0 (11.5) | −2.071 | 0.038 |
Light avoidance | DL1 time (s) | 43.0 (20.0) | 37.5 (64.5) | −0.352 | 0.725 |
LD time (s) | 6.0 (3.0) | 17.5 (10.75) | −5.065 | <0.001 | |
DL2 time (s) | 97.0 (70.0) | 20.0 (78.0) | −3.226 | 0.001 | |
Open-Field | Rearings (n) | 35.0 (8.0) | 8.0 (9.25) | −2.696 | 0.007 |
Urine Drops (n) | 0.0 (0.0) | 0.0 (0.0) | −0.961 | 0.337 | |
Fecal pellets (n) | 0.0 (1.0) | 0.0 (1.25) | −0.103 | 0.918 | |
Distance (cm) | 959.0 (522.0) | 1032.0 (525.75) | −1.056 | 0.291 | |
Resting time (s) | 44.0 (57.0) | 78.0 (76.25) | −1.669 | 0.095 | |
Olfactory preference- Control | Water (left side): Latency to sniff (s) | 31.0 (19.0) | 27.0 (40.0) | −1.613 | 0.107 |
Water (left side): Number of sniffs (n) | 2.0 (1.0) | 2.0 (4.5) | −1.062 | 0.288 | |
Water (left side): Distance (cm) | 24.0 (17.0) | 24.0 (36.5) | −0.789 | 0.430 | |
Water (right side): Latency to sniff (s) | 36.0 (24.0) | 26.0 (26.0) | −2.015 | 0.044 | |
Water (right side): Number of sniffs (n) | 2.0 (2.0) | 2.0 (4.5) | −1.176 | 0.240 | |
Water (right side): Distance (cm) | 25.0 (21.0) | 27.0 (44.0) | −1.260 | 0.208 | |
Total distance (cm) | 978.0 (270.0) | 1110.0 (511.0) | −1.821 | 0.069 | |
Olfactory preference- Odor | Water: Latency to sniff (s) | 55.0 (63.0) | 80.0 (150.0) | −0.502 | 0.616 |
Water: Number of sniffs (n) | 1.0 (1.0) | 1.0 (2.0) | −0.233 | 0.816 | |
Water: Distance (cm) | 17.0 (11.0) | 12.0 (45.5) | −0.277 | 0.820 | |
Odour: Latency to sniff (s) | 31.0 (17.0) | 21.0 (37.0) | −1.647 | 0.100 | |
Odour: Number of sniffs (n) | 2.0 (1.0) | 2.0 (2.0) | −0.538 | 0.591 | |
Odour: Distance (cm) | 26.0 (16.0) | 25.0 (41.5) | −0.353 | 0.724 | |
Total distance (cm) | 1054.0 (266.0) | 895.0 (372.5) | −2.103 | 0.035 | |
Olfactory preference- Urine | Water: Latency to sniff (s) | 57.0 (49.0) | 54.0 8160.5) | −0.261 | 0.794 |
Water: Number of sniffs (n) | 1.0 (1.0) | 1.0 (1.5) | −0.991 | 0.322 | |
Water: Distance (cm) | 21.0 (15.0) | 12.0 (22.5) | −1.283 | 0.200 | |
Urine: Latency to sniff (s) | 44.0 (31.0) | 24.0 (80.5) | −2.400 | 0.016 | |
Urine: Number of sniffs (n) | 2.0 (1.0) | 2.0 (2.0) | −1.920 | 0.055 | |
Urine: Distance (cm) | 24.0 (13.0) | 36.0 (34.0) | −1.389 | 0.165 | |
Total distance (cm) | 952.0 (192.0) | 970.0 (308.5) | −0.576 | 0.565 |
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Bontempi, P.; Ricatti, M.J.; Sandri, M.; Nicolato, E.; Mucignat-Caretta, C.; Zancanaro, C. Age-Related In Vivo Structural Changes in the Male Mouse Olfactory Bulb and Their Correlation with Olfactory-Driven Behavior. Biology 2023, 12, 381. https://doi.org/10.3390/biology12030381
Bontempi P, Ricatti MJ, Sandri M, Nicolato E, Mucignat-Caretta C, Zancanaro C. Age-Related In Vivo Structural Changes in the Male Mouse Olfactory Bulb and Their Correlation with Olfactory-Driven Behavior. Biology. 2023; 12(3):381. https://doi.org/10.3390/biology12030381
Chicago/Turabian StyleBontempi, Pietro, Maria Jimena Ricatti, Marco Sandri, Elena Nicolato, Carla Mucignat-Caretta, and Carlo Zancanaro. 2023. "Age-Related In Vivo Structural Changes in the Male Mouse Olfactory Bulb and Their Correlation with Olfactory-Driven Behavior" Biology 12, no. 3: 381. https://doi.org/10.3390/biology12030381
APA StyleBontempi, P., Ricatti, M. J., Sandri, M., Nicolato, E., Mucignat-Caretta, C., & Zancanaro, C. (2023). Age-Related In Vivo Structural Changes in the Male Mouse Olfactory Bulb and Their Correlation with Olfactory-Driven Behavior. Biology, 12(3), 381. https://doi.org/10.3390/biology12030381