We have approached the question of the reliability of the thymidine labeling index (TLI) of breast carcinoma by comparing paired samples. Because the distribution of the TLI is approximately lognormal, comparisons were made after transformation to the natural logarithm. For 38 paired samples from the primary carcinoma (biopsy versus residual tumor in mastectomy specimen), r, 0.89, p less than 0.0001. For 68 primary carcinomas versus their axillary metastases, r, 0.90, p less than 0.0001. Substantial correlation was also observed between the TLIs of 18 primary breast carcinomas and their recurrent or metastatic lesions studied after relapse (r, 0.75, p less than 0.0003), and between 14 pairs of first and second primary carcinomas recovered from the same breast (r, 0.72, p less than 0.003). Good agreement was achieved among three observers in measuring the TLI from a set of breast carcinoma autoradiographs. We conclude that the TLI is sufficiently reliable for semiquantitative use as a means of separating breast carcinomas into groups with slow, moderate, and rapid rates of proliferation. The substantial similarities between the TLIs of breast carcinoma samples from different sites of the primary tumor, between primary tumor and axillary metastases, and between primary tumor and subsequent samples of relapsed tumor suggest that clonal evolution either is infrequent or does not usually affect the cell kinetics of the carcinoma. The similarity of the TLIs of synchronous dual primary carcinomas is an additional interesting finding.
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J Med Internet Res
January 2025
Cancer Screening, American Cancer Society, Atlanta, GA, United States.
Background: The online nature of decision aids (DAs) and related e-tools supporting women's decision-making regarding breast cancer screening (BCS) through mammography may facilitate broader access, making them a valuable addition to BCS programs.
Objective: This systematic review and meta-analysis aims to evaluate the scientific evidence on the impacts of these e-tools and to provide a comprehensive assessment of the factors associated with their increased utility and efficacy.
Methods: We followed the 2020 PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and conducted a search of MEDLINE, PsycINFO, Embase, CINAHL, and Web of Science databases from August 2010 to April 2023.
Cien Saude Colet
January 2025
Universidade Federal do Ceará. R. Alexandre Baraúna 1115, Rodolfo Teófilo. 60430-160 Fortaleza CE Brasil.
Mammography is one of the main methods available for breast cancer screening in Brazil. However, differences in timely access and performance of the exam can be highlighted based on social determinants of health, considered relevant due to their influence on the health situation of a population. Thus, the present study aimed to identify the social determinants of health associated with access to and performance of mammography in Brazilian women.
View Article and Find Full Text PDFCien Saude Colet
January 2025
Instituto René Rachou, Fundação Oswaldo Cruz (Fiocruz Minas). Av. Augusto de Lima 1715, Barro Preto. 30190-002 Belo Horizonte MG Brasil.
This article aims to identify the relationship between material deprivation and mortality from breast, cervical, and prostate neoplasms in the Brazilian adult population and the relationship between ethnicity/skin color and material deprivation. This cross-sectional ecological study calculated the mean mortality rate per 100,000 inhabitants, and deaths were standardized by age and gender and redistributed per to ill-defined causes, stratified by age group and ethnicity/skin color. We applied the Negative Binomial model, containing the interaction between ethnicity/skin color and the Brazilian Deprivation Index (IBP).
View Article and Find Full Text PDFBrief Bioinform
November 2024
Center for Artificial Intelligence Research, Wake Forest University School of Medicine, Winston-Salem, NC 27101, United States.
Pathway analysis plays a critical role in bioinformatics, enabling researchers to identify biological pathways associated with various conditions by analyzing gene expression data. However, the rise of large, multi-center datasets has highlighted limitations in traditional methods like Over-Representation Analysis (ORA) and Functional Class Scoring (FCS), which struggle with low signal-to-noise ratios (SNR) and large sample sizes. To tackle these challenges, we use a deep learning-based classification method, Gene PointNet, and a novel $P$-value computation approach leveraging the confusion matrix to address pathway analysis tasks.
View Article and Find Full Text PDFMol Biol Rep
January 2025
Department of Biology, Central Tehran Branch, Islamic Azad University, Tehran, Iran.
Background: Breast carcinoma stands out as the most widespread invasive cancer and the top contributor to cancer-related mortality in women. Nanoparticles have emerged as promising tools in cancer detection, diagnosis, and prevention. In this study, the antitumor and apoptotic capability of silver nanoparticles synthesized through Scrophularia striata extract (AgNPs-SSE) was investigated toward breast cancer cells.
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