Titre : Nucléosomes

Nucléosomes : Questions médicales fréquentes

Termes MeSH sélectionnés :

Prostatic Neoplasms

Questions fréquentes et termes MeSH associés

Diagnostic 2

#1

Comment identifier les nucléosomes dans une cellule ?

Les nucléosomes peuvent être identifiés par des techniques comme l'électrophorèse sur gel.
Nucléosomes Électrophorèse ADN
#2

Quels tests détectent les niveaux de nucléosomes ?

Des tests sanguins mesurant les niveaux de nucléosomes libres sont utilisés en clinique.
Nucléosomes Tests sanguins Biomarqueurs

Symptômes 2

#1

Les nucléosomes sont-ils associés à des symptômes ?

Les nucléosomes eux-mêmes ne causent pas de symptômes, mais leur dysfonction peut être liée à des maladies.
Nucléosomes Maladies Dysfonction
#2

Quels troubles sont liés aux anomalies des nucléosomes ?

Des anomalies des nucléosomes sont associées à des cancers et des maladies auto-immunes.
Nucléosomes Cancers Maladies auto-immunes

Prévention 2

#1

Peut-on prévenir les anomalies des nucléosomes ?

Une alimentation saine et un mode de vie actif peuvent réduire le risque de maladies associées.
Nucléosomes Prévention Mode de vie
#2

Y a-t-il des dépistages pour les problèmes de nucléosomes ?

Actuellement, il n'existe pas de dépistage spécifique pour les anomalies des nucléosomes.
Nucléosomes Dépistage Anomalies

Traitements 2

#1

Comment traiter les maladies liées aux nucléosomes ?

Le traitement dépend de la maladie sous-jacente, incluant chimiothérapie ou immunothérapie.
Nucléosomes Chimiothérapie Immunothérapie
#2

Les médicaments ciblent-ils les nucléosomes ?

Certains médicaments visent les voies de signalisation affectées par les nucléosomes.
Nucléosomes Médicaments Voies de signalisation

Complications 2

#1

Quelles complications peuvent survenir avec des nucléosomes anormaux ?

Des nucléosomes anormaux peuvent entraîner des cancers et des troubles immunitaires.
Nucléosomes Complications Cancers
#2

Les nucléosomes affectent-ils la réparation de l'ADN ?

Oui, des anomalies dans les nucléosomes peuvent perturber les mécanismes de réparation de l'ADN.
Nucléosomes Réparation de l'ADN Anomalies

Facteurs de risque 2

#1

Quels facteurs augmentent le risque d'anomalies des nucléosomes ?

Des facteurs comme l'exposition à des toxines et des prédispositions génétiques augmentent le risque.
Nucléosomes Facteurs de risque Toxines
#2

L'âge influence-t-il les nucléosomes ?

Oui, le vieillissement peut affecter la structure et la fonction des nucléosomes.
Nucléosomes Âge Vieillissement
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Dr Olivier Menir

Contenu validé par Dr Olivier Menir

Expert en Médecine, Optimisation des Parcours de Soins et Révision Médicale


Validation scientifique effectuée le 04/03/2026

Contenu vérifié selon les dernières recommandations médicales

Auteurs principaux

Hitoshi Kurumizaka

6 publications dans cette catégorie

Affiliations :
  • Laboratory of Chromatin Structure and Function, Institute for Quantitative Biosciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo 113-0032, Japan. Electronic address: kurumizaka@iam.u-tokyo.ac.jp.

Karolin Luger

4 publications dans cette catégorie

Publications dans "Nucléosomes" :

Vladimir B Teif

4 publications dans cette catégorie

Affiliations :
  • School of Life Sciences, University of Essex, Wivenhoe Park, Colchester, CO4 3SQ, UK. vteif@essex.ac.uk.

Felix Mueller-Planitz

3 publications dans cette catégorie

Affiliations :
  • Institute of Physiological Chemistry, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany. felix.mueller-planitz@tu-dresden.de.
Publications dans "Nucléosomes" :

Tomoya Kujirai

3 publications dans cette catégorie

Affiliations :
  • Laboratory of Chromatin Structure and Function, Institute for Quantitative Biosciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo 113-0032, Japan.
Publications dans "Nucléosomes" :

Andrea Schmid

3 publications dans cette catégorie

Affiliations :
  • Biomedical Center (BMC), Molecular Biology, Faculty of Medicine, LMU Munich, Planegg-Martinsried, 82152 Munich, Germany.
Publications dans "Nucléosomes" :

Philipp Korber

3 publications dans cette catégorie

Affiliations :
  • Biomedical Center (BMC), Molecular Biology, Faculty of Medicine, LMU Munich, Planegg-Martinsried, 82152 Munich, Germany.
Publications dans "Nucléosomes" :

Ayako Furukawa

3 publications dans cette catégorie

Affiliations :
  • Graduate School of Medical Life Science, Yokohama City University, 1-7-29 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan.

Yasuhiro Arimura

3 publications dans cette catégorie

Affiliations :
  • Laboratory of Chromatin Structure and Function, Institute for Quantitative Biosciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo 113-0032, Japan.

Yasuo Tsunaka

3 publications dans cette catégorie

Affiliations :
  • Graduate School of Medical Life Science, Yokohama City University, 1-7-29 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan.

Yoshifumi Nishimura

3 publications dans cette catégorie

Affiliations :
  • Graduate School of Medical Life Science, Yokohama City University, 1-7-29 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan.
  • Graduate School of Integrated Sciences for Life, Hiroshima University, 1-4-4 Kagamiyama, Higashi-Hiroshima 739-8258, Japan.

Tae-Hee Lee

3 publications dans cette catégorie

Publications dans "Nucléosomes" :

Petra Vizjak

2 publications dans cette catégorie

Affiliations :
  • Institute of Physiological Chemistry, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.
  • Department of Molecular Biology, Biomedical Center, Faculty of Medicine, Ludwig-Maximilians-Universität München, Planegg-Martinsried, Germany.
  • Early Stage Bioprocess Development, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riss, Germany.
Publications dans "Nucléosomes" :

Dieter Kamp

2 publications dans cette catégorie

Affiliations :
  • Gene Center, Department of Biochemistry, Ludwig-Maximilians-Universität München, Munich, Germany.
Publications dans "Nucléosomes" :

Nicola Hepp

2 publications dans cette catégorie

Affiliations :
  • Institute of Physiological Chemistry, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.
  • Department of Molecular Biology, Biomedical Center, Faculty of Medicine, Ludwig-Maximilians-Universität München, Planegg-Martinsried, Germany.
  • Department of Clinical Genetics, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark.
Publications dans "Nucléosomes" :

Alessandro Scacchetti

2 publications dans cette catégorie

Affiliations :
  • Department of Molecular Biology, Biomedical Center, Faculty of Medicine, Ludwig-Maximilians-Universität München, Planegg-Martinsried, Germany.
  • Epigenetics Institute and Department of Cell and Developmental Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Publications dans "Nucléosomes" :

Mariano Gonzalez Pisfil

2 publications dans cette catégorie

Affiliations :
  • Core Facility Bioimaging and Walter-Brendel-Centre of Experimental Medicine, Biomedical Center, Ludwig-Maximilians-Universität München, Planegg-Martinsried, Germany.
Publications dans "Nucléosomes" :

Joseph Bartho

2 publications dans cette catégorie

Affiliations :
  • Gene Center, Department of Biochemistry, Ludwig-Maximilians-Universität München, Munich, Germany.
  • European Molecular Biology Laboratory, Heidelberg, Germany.
Publications dans "Nucléosomes" :

Mario Halic

2 publications dans cette catégorie

Affiliations :
  • Department of Structural Biology, St. Jude Children's Research Hospital, Memphis, TN, USA.
Publications dans "Nucléosomes" :

Sources (9751 au total)

Completeness of variables in Hospital-Based Cancer Registries for prostatic malignant neoplasm.

to analyze the completeness of variables from Hospital-Based Cancer Registries of cases of prostate neoplasm in the Oncology Care Network of a Brazilian state between 2000 and 2020.... an ecological time series study, based on secondary data on prostate cancer Hospital-Based Cancer Registries prostate. Data incompleteness was classified as excellent (<5%), good (between 5%-10%), fai... there were 13,519 cases of prostate cancer in the Hospital-Based Cancer Registries analyzed. The variables "family history of cancer" (p<0.001), "alcoholism" (p<0.001), "smoking" (p<0.001), "TNM stagi... most Hospital-Based Cancer Registries variables showed excellent completeness, but important variables had high percentages of incompleteness, such as TNM and clinical staging, in addition to alcoholi...

Prostate health index (PHI) as an accurate prostate cancer predictor.

This study aims to compare the ability of the PHI versus tPSA test to predict the presence of PCa in our population.... A prospective observational study was performed. We included patients with tPSA ≥ 2.5 ng/ml, biopsy naïve or previous negative biopsy, undergoing a blood test, which includes tPSA, fPSA, and p2PSA, an... 140 men were included. Fifty-seven (40.7%) had a positive prostate biopsy result (Group A), and 83 (59.3%) had a negative biopsy result (Group B). The mean age was similar in both groups (mean ± stand... The PHI test improves PCa detection compared to tPSA in our population....

Automatic detection of prostate cancer grades and chronic prostatitis in biparametric MRI.

With emerging evidence to improve prostate cancer (PCa) screening, multiparametric magnetic prostate imaging is becoming an essential noninvasive component of the diagnostic routine. Computer-aided di... We collected 1647 fine-grained biopsy-confirmed findings, including Gleason scores and prostatitis, to form a training dataset. In our experimental framework for lesion detection, all models utilized ... An optimal model configuration with fine class granularity (prostatitis included) and OHE has scored the lesion-wise partial Free-Response Receiver Operating Characteristic (FROC) area under the curve... This paper examines several configurations for model training in the biparametric MRI setup and proposes optimal value ranges. It also shows that the fine-grained class configuration, including prosta...

Is prostatic adenocarcinoma with cribriform architecture more difficult to detect on prostate MRI?

Cribriform (CBFM) pattern on prostate biopsy has been implicated as a predictor for high-risk features, potentially leading to adverse outcomes after definitive treatment. This study aims to investiga... Patients who underwent multiparametric magnetic resonance imaging (mpMRI), combined 12-core transrectal ultrasound (TRUS) guided systematic (SB) and MRI/US fusion-guided biopsy were retrospectively qu... Between 2015 and 2022, a total of 131 consecutive patients with CBFM pattern on prostate biopsy and pre-biopsy mpMRI were included. Clinical feature analysis included 1572 systematic biopsy cores (114... The extent of disease for CBFM-containing tumors is difficult to capture on mpMRI. When comparing MRI lesions of similar dimensions and PIRADS scores, CBFM-containing tumors appear to have larger canc...

Development and evaluation of the MiCheck® Prostate test for clinically significant prostate cancer.

There is a clinical need to identify patients with an elevated PSA who would benefit from prostate biopsy due to the presence of clinically significant prostate cancer (CSCaP). We have previously repo... To further develop and adapt the MiCheck® Prostate test so it can be performed using a standard clinical chemistry analyzer and characterize its performance using the MiCheck-01 clinical trial sample ... About 358 patient samples from the MiCheck-01 US clinical trial were used for the development of the MiCheck® Prostate test. These consisted of 46 controls, 137 non-CaP, 62 non-CSCaP, and 113 CSCaP.... Serum analyte concentrations for cellular growth factors were determined using custom-made Luminex-based R&D Systems multi-analyte kits. Analytes that can also be measured using standard chemistry ana... Logistic regression modeling with Monte Carlo cross-validation was used to identify Human Epidydimal Protein 4 (HE4) as an analyte able to significantly improve the algorithm specificity at 95% sensit... The MiCheck® logistic regression model was developed and consisted of PSA, %free PSA, DRE, and HE4. The model differentiated clinically significant cancer from no cancer or not-clinically significant ... The MiCheck® Prostate test identifies clinically significant prostate cancer with high sensitivity and negative predictive value (NPV). It can be performed in a clinical laboratory using a Roche Cobas...