Automated quantification of dopaminergic immunostained neurons in substantia nigra using freely available software.
Computerized techniques for image analysis are critical for progress in cell biology. The complexity of the data in current methods eliminates the need for manual image analysis and usually requires the application of multiple algorithms sequentially to the images. Our aim was to develop a software...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 60; no. 10; pp. 2995 - 3008 |
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| Autores principales: | , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Oct2022
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=159003933&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 159003933 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Oct2022 vid: 60 iid: 10 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 159003933 158717323 159003933 NLM36018532 10.1007/s11517-022-02643-8 NLM36018532 159003933 ppf: 2995 ppct: 13 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Automated quantification of dopaminergic immunostained neurons in substantia nigra using freely available software. aug: au: Bonaccorso Marinelli, María Paula Baiardi, Gustavo Valdez, Susana Ruth Cabrera, Ricardo Jorge affil: Instituto de Investigaciones Biomédicas (INBIOMED), Universidad de Mendoza, Huarpes 630, 5500, Mendoza, Argentina sug: subj: Oxidoreductases Metabolism Neurons Metabolism Animals Dopamine Male Rats Software Brain Stem Metabolism Brain Stem Pathology Male ab: Computerized techniques for image analysis are critical for progress in cell biology. The complexity of the data in current methods eliminates the need for manual image analysis and usually requires the application of multiple algorithms sequentially to the images. Our aim was to develop a software for immunohistochemical analysis of brain dopaminergic neurons combining several computational approaches to automatically analyze and quantify their number in the substantia nigra after a neurotoxic injury. For this purpose, we used a Parkinson's disease animal model to test our application. The dopaminergic neurotoxin, 6-hydroxydopamine, was administered in adult male rats to damage dopaminergic neurons in substantia nigra and to induce hemiparkinsonism. The lesion was corroborated by behavioral evaluation in response to apomorphine and amphetamine. The animals were euthanized and their brains processed for tyrosine hydroxylase immunohistochemistry for dopamine neuron identification. Neurons positive for tyrosine hydroxylase were evaluated in substantia nigra by light microscopy. The images were used to show quantification applicability. To test our software counting accuracy and validity, automatic dopamine neuron number was correlated with the data obtained by three independent observers. Several parameters were used to depict neuronal function in dataset images from control and lesioned brains. In conclusion, we could perform an automated quantification of dopaminergic neurons and corroborate the validity and accuracy of a freely available software. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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