Bibliographic record
Abstract
Hepatocellular carcinoma (HCC) is the most common malignant tumor of males in the world, with an incidence of 1,000,000 new cases a year. It is endemic in Southeast Asia and Sub-Saharan Africa. Risk factors include chronic infection with hepatitis B virus (HBV) and hepatitis C virus (HCV), Aflatoxin B1 uptake, hemochromatosis, and alpha1 -antitripsin deficiency. Epidemiological studies provide evidence for the association of HCC with HBV infection. The incidence of HCC is high in regions hyperendemic for HBV. Chronic carrier state and maternal-infant transmission are important factors in the development of HCC. Evidence of direct oncogenic effect of H BV is well established, HCCs contain viral DNA sequences integrated into hepatocyte DNA that act as random insertional mutagens, and these sites are near genes involved in the control of proliferation and differentiation. The mechanism of hepatitis C virus in hepatocarcinogenesis is still imprecise but a high percentage of cases are related to this virus. Chronic alcohol consumption and cirrhosis are cofactors that increase the development of HCC in patients with chronic viral infection. In experimental carcinogenesis a multipotential element called oval cell proliferates in the early stages. The cellular events are accompanied by increased expression of several growth factors that enhance the survival of carcinogen-activated cells by suppressing apoptosis and increasing elements entering the cell cycle. Hepatic carcinogenesis is a complex process associated with accumulation of genetic and epigenetic changes that run through steps of initiation, promotion and progression. Activation of oncogenes of the "ras" family and others has been detected during chemically-induced HCC in rodents, but there is little evidence of such activation in human tumors. The role of tumor supressor genes such as retinoblastoma (RB) and P53 genes has been documented. Aflatoxin B1 that contaminates foods in endemic areas has a clear role in hepatocarcinogenesis. Metabolites of this toxin promote apurinic sites and G to T mutations in chromosomal DNA, the third base of codon 249 of the P53 gene is preferentially targeted to form aducts with aflatoxin B1, and this mutation has been specifically identified in HBV infection. Histological and cytological criteria for the diagnosis of HCC are well established and are based in architectural and cytological changes. An important issue is the diagnosis of liver "nodules" detected by image, from which small biopsies or aspiration material is obtained. Special studies such as reticulin, CD34, cytokeratin profile, and MOC-31 can be very useful for the differential diagnosis of primary and metastatic tumors. Telomerase activity has been found in HCC and negative in pericancerous tissue. It is more pronounced in poorly differentiated tumors and correlates with factors of clinical importance, such as prognosis and recurrences. Cells of well-differentiated HCC have an ultrastructural appearance similar to normal hepatocytes. During the process of dedifferentiation, there is progressive loss of organization of intracellular organelles. The cell cohesion is lost, intercellular gaps with microvilli appear, the sinusoids become capillarized, and reparative changes are seen in the spaces of Disse. A variety of inclusions, such as Mallory bodies, granular material, secondary lysosomes, and Dubin-Johnson pigment, have been described. Fibrolamellar carcinoma has a characteristic histological picture and ultrastructurally oncocytic features. Neuroendocrine granules and combination of HCC with bile duct carcinoma are seen by electron microscopy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.006 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".