Evidence map›Paper›PMID 12141830›Full record

ArticleDigestive diseases and sciences2002

Digital image analysis of the distribution of proliferating cell nuclear antigen in hepatitis C virus-related chronic hepatitis, cirrhosis, and hepatocellular carcinoma.

Gerond Lake-Bakaar, Vito Mazzoccoli, Lynda Ruffini

Abstract read
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In one paragraph

Article in Digestive diseases and sciences, 2002. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.4field-weighted citation impact, top 37% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 12 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Gerond Lake-BakaarDepartment of Medicine, VA Medical Center, Northport, New York 11768, USA.
Vito Mazzoccoli
Lynda Ruffini
Northport VA Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Viral dynamic studies in chronic hepatitis C virus (HCV) infection indicate a significantly shortened survival of virus-infected cells. Since at the steady state of chronic viral infection, the rate of infected cell elimination equals new cell regeneration, this would imply a high rate of hepatocyte turnover in chronic HCV liver disease. We estimated the fraction of regenerating hepatocytes in liver biopsy sections in chronic HCV liver disease, cirrhosis, and hepatocellular carcinoma (HCC). We used antibodies to proliferating cell nuclear antigen (PCNA) to detect proliferating cell nuclei in liver biopsy specimen from controls and patients with chronic hepatitis, cirrhosis, and HCC. We also used bis-benzimide to label fluorescently all hepatocyte nuclei simultaneously. Using digital image analysis, we calculated the area occupied by PCNA-stained hepatocyte nuclei, as a fraction of the total area occupied by fluorescently labeled hepatocyte nuclei (labeling index; LI). Antibody staining was negligible in the control specimen. The mean +/- SE PCNA LI increased from 0.21 +/- 0.1 in chronic hepatitis to 0.63 +/- 0.15 in HCC. There was no significant difference between chronic hepatitis and cirrhosis. The fraction of cells undergoing regeneration is increased in chronic HCV liver disease, HCV-related cirrhosis, and HCC. Increased hepatocyte turnover could provide the link between chronic HCV liver disease and HCC.

Indexed as

Image Processing, Computer-AssistedCarcinoma, HepatocellularHepatitis C, ChronicHepatocytesHumansImmunohistochemistryLiverLiver CirrhosisLiver NeoplasmsProliferating Cell Nuclear AntigenProliferating Cell Nuclear Antigen

Identifiers

PMID12141830
OpenAlexW347687221

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.