0000000000069716

AUTHOR

Timo Ylikomi

showing 3 related works from this author

Inducibility of the avidin gene by progesterone is suppressed during estrogen-induced cytodifferentiation.

1992

Abstract We have studied epithelial differentiation of the chick oviduct as induced by diethylstilbestrol (DES) and 17β-estradiol (E 2 ). The proportion of goblet cells in the oviduct was slightly higher after E 2 than after DES treatment. Also avidin induction by progesterone was stronger following DES than E 2 priming. In the estrogen pretreated oviduct epithelium, avidin expression was induced by progesterone in the surface epithelial cells, protodifferentiated gland cells and tubular gland cells, but not in goblet cells. During prolonged estrogen treatment, however, the inducibility of avidin by progesterone ceased in tubular gland cells but not in surface epithelial cells. The estrogen…

medicine.medical_specialtymedicine.drug_classOvalbuminEndocrinology Diabetes and MetabolismClinical BiochemistryDiethylstilbestrolEstrogen receptorOviductsBiologyBiochemistryEpitheliumImmunoenzyme TechniquesEndocrinologystomatognathic systemInternal medicineProgesterone receptormedicineAnimalsTubular glandMolecular BiologyDiethylstilbestrolIn Situ HybridizationProgesteroneEstradiolCell DifferentiationEpithelial CellsCell BiologyAvidinEpitheliummedicine.anatomical_structureEndocrinologyGene Expression RegulationEstrogenbiology.proteinMolecular MedicineOviductChickenshormones hormone substitutes and hormone antagonistsmedicine.drugAvidinThe Journal of steroid biochemistry and molecular biology
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Multilabel segmentation of cancer cell culture on vascular structures with deep neural networks

2020

New increasingly complex in vitro cancer cell models are being developed. These new models seem to represent the cell behavior in vivo more accurately and have better physiological relevance than prior models. An efficient testing method for selecting the most optimal drug treatment does not exist to date. One proposed solution to the problem involves isolation of cancer cells from the patients' cancer tissue, after which they are exposed to potential drugs alone or in combinations to find the most optimal medication. To achieve this goal, methods that can efficiently quantify and analyze changes in tested cell are needed. Our study aimed to detect and segment cells and structures from canc…

Paperneural networkImage Processing3122 CancersComputational biologyneuroverkotmikroskopia030218 nuclear medicine & medical imaging03 medical and health sciences0302 clinical medicineIn vivoLNCaPmedicinecancerRadiology Nuclear Medicine and imagingSegmentationErrataContextual image classificationbusiness.industrysegmentationCancerin vitroImage segmentationmedicine.diseasesoluviljelysegmentointisyöpäsolutkuvantaminenin vitro -menetelmäCell culture030220 oncology & carcinogenesisCancer cellmicroscopy3111 Biomedicinebusiness
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Quantification of vesicles in differentiating human SH-SY5Y neuroblastoma cells by automated image analysis

2005

A new automated image analysis method for quantification of fluorescent dots is presented. This method facilitates counting the number of fluorescent puncta in specific locations of individual cells and also enables estimation of the number of cells by detecting the labeled nuclei. The method is here used for counting the AM1-43 labeled fluorescent puncta in human SH-SY5Y neuroblastoma cells induced to differentiate with all-trans retinoic acid (RA), and further stimulated with high potassium (K+) containing solution. The automated quantification results correlate well with the results obtained manually through visual inspection. The manual method has the disadvantage of being slow, labor-i…

Pathologymedicine.medical_specialtyBiologySensitivity and SpecificityPattern Recognition AutomatedNeuroblastoma cellNeuroblastomaFuzzy LogicArtificial IntelligenceCell Line TumorImage Interpretation Computer-AssistedmedicineHumansSegmentationTransport VesiclesAnalysis methodSh sy5y neuroblastomaGeneral NeuroscienceVesicleReproducibility of ResultsCell DifferentiationImage segmentationFluorescenceCell Transformation NeoplasticMicroscopy FluorescenceAlgorithmsBiomedical engineeringAutomated methodNeuroscience Letters
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