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Quantitative expression of estrogen, progesterone and human epidermal growth factor receptor-2 and their correlation with immunohistochemistry in breast cancer at Uganda Cancer Institute.
PLoS One
January 2025
Department of Clinical Support Services, Division of Laboratory and Pathology Medicine, Uganda Cancer Institute, Kampala, Uganda.
The detection of Estrogen Receptor (ER), Progesterone Receptor (PR), and Human epidermal growth factor receptor 2 (HER-2) is important for the stratification of breast cancer and the selection of therapeutic modalities. This study aimed to determine the quantitative expression of ER, PR and HER-2 using Immunohistochemistry and their correlation with quantitative baseline Ct values measured using Quantitative Polymerase Chain Reaction (PCR). This study also assessed the use of fresh breast tissue biopsies preserved in RNAlater solution in the quantitative detection of these receptors using PCR technique.
View Article and Find Full Text PDFPredicting noncoding RNA and disease associations using multigraph contrastive learning.
Sci Rep
January 2025
College of Information Science Technology, Hainan Normal University, Haikou, 571158, China.
MiRNAs and lncRNAs are two essential noncoding RNAs. Predicting associations between noncoding RNAs and diseases can significantly improve the accuracy of early diagnosis.With the continuous breakthroughs in artificial intelligence, researchers increasingly use deep learning methods to predict associations.
View Article and Find Full Text PDFTB or not TB? Development and validation of a clinical decision support system to inform airborne isolation requirements in the evaluation of suspected tuberculosis.
Infect Control Hosp Epidemiol
January 2025
Division of Infectious Diseases, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.
Background: The study objective was to develop and validate a clinical decision support system (CDSS) to guide clinicians through the diagnostic evaluation of hospitalized individuals with suspected pulmonary tuberculosis (TB) in low-prevalence settings.
Methods: The "TBorNotTB" CDSS was developed using a modified Delphi method. The CDSS assigns points based on epidemiologic risk factors, TB history, symptoms, chest imaging, and sputum/bronchoscopy results.
Causal factors identification and dynamics simulation of major road traffic accidents from China's evidence: A high-order mixed-method design.
Accid Anal Prev
December 2024
School of Civil Engineering and Transportation, Northeast Forestry University, Harbin 150040, Heilongjiang, China.
Mitigating the injury and severity of road traffic accidents has become a crucial objective in global road safety efforts. Major road traffic accidents (MRTAs) pose significant challenges due to their high hazard and severe consequences. Despite their widespread impact, the complex causation mechanisms behind MRTAs have not been thoroughly and systematically investigated, which hinders the development of effective control strategies and policies.
View Article and Find Full Text PDFA hybrid model for refining gross primary productivity estimation by integrating multiple environmental factors.
MethodsX
June 2025
State Key Laboratory of Remote Sensing Science, Beijing Normal University, Beijing 100875, China.
Environmental factors lead mainly to the uncertainty of gross primary productivity estimation in most light use efficiency (LUE, ε) models since the simple physical formulas are inadequate to fully express the overall constraint of diverse environmental factors on the maximum ε (ε). In contrast, machine learning has the natural potential to detect intricate patterns and relationships among various environmental variables. Here, we presented a hybrid model (TL-CRF) that utilizes the random forest (RF) technique to incorporate various ecological stress factors into the two-leaf LUE (TL-LUE) model, meanwhile, seasonal differences in the clumping index (CI) on a global scale are considered to adjust seasonal patterns of canopy structure.
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