metadata
datasets:
- allenai/scifact
widget:
- text: >-
X-linked genes, particularly those related to chromatin
structure/remodeling, segregation, and ribosomal biogenesis and
translational control, may also play key regulatory roles in breast
carcinogenesis<SEP>While contribution of X chromosome in the
susceptibility of prostate and ovarian cancer has been demonstrated, the
role of X-linked genes in breast carcinogenesis is not clearly known. This
study investigated and compared the X-linked gene expression profiles of
MMTV-c-myc transgenic mammary tumor (MT) or MMTV-c-myc/MT-tgf-alpha double
transgenic mouse mammary tumor (DT) to lactating mammary gland. cDNA
microarray analysis using the Affymetrix system identified 1081 genes
localized on the X chromosome with 174 and 194 genes at +/-2-fold change
levels in MT and DT samples, respectively. Differentially expressed
X-linked genes were predominantly related to chromatin
structure/remodeling (e.g., Hdac8, Suv39h1, RbAp46 and Adr1), segregation
(e.g., CENP-I and smc111) and, ribosomal biogenesis and translational
control (e.g., Dkc1, Rpl44, Rpl39, Eif2s3x, Gspt2 and Rsk4). Confirmation
of microarray data by semi-quantitative and quantitative RT-PCR in
selected X-linked genes also showed similar pattern. In addition, the
expression pattern of two chromosomal regions, XE3 and XF5, suggests that
XE3 may have escaped from inactivation and XF5 subjected to inactivation.
In conclusion, our data suggest that X-linked genes may play the key
regulatory roles in the maintenance of chromatin structure, accurate
chromosomal segregation and translational control; hence deregulation of
X-linked genes may promote mammary gland tumorigenesis by promoting
genetic instability and cell proliferation. Increased understanding of the
role of X-linked genes and genetic pathways will provide the strategies to
develop the molecular therapeutics to treat and prevent reproductive
related cancers.
language:
- en
metrics:
- accuracy
- f1
- precision
- recall
tags:
- medical
Textual Entailment for biomedical texts
Model Description
This model is fine-tuned on SciFact dataset for textual antailment task in the domain of biomedicine.