98%
921
2 minutes
20
In past quarter of the century, much has been understood about the genetic variation and abnormal genes that activate cancer in humans. All the cancers somehow possess alterations in the DNA sequence of cancer cell's genome. In present, we are heading toward the era where it is possible to obtain complete genome of the cancer cells for their better diagnosis, categorization and to explore treatment options.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1007/978-3-031-27156-4_2 | DOI Listing |
JMIR Med Inform
September 2025
Global Health Economics Centre, Public Health and Policy, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Background: Artificial intelligence (AI) algorithms offer an effective solution to alleviate the burden of diabetic retinopathy (DR) screening in public health settings. However, there are challenges in translating diagnostic performance and its application when deployed in real-world conditions.
Objective: This study aimed to assess the technical feasibility of integration and diagnostic performance of validated DR screening (DRS) AI algorithms in real-world outpatient public health settings.
Nano Lett
September 2025
School of Materials and Chemistry, University of Shanghai for Science & Technology, Shanghai 200093, China.
Developing low-temperature gas sensors for parts per billion-level acetone detection in breath analysis remains challenging for non-invasive diabetes monitoring. We implement dual-defect engineering via one-pot synthesis of Al-doped WO nanorod arrays, establishing a W-O-Al catalytic mechanism. Al doping induces lattice strain to boost oxygen vacancy density by 31.
View Article and Find Full Text PDFBrain Behav
September 2025
Department of Neurosurgery, First Medical Center of the Chinese PLA General Hospital, Beijing, People's Republic of China.
Background: The gut microbiota plays a crucial role in the development of glioma. With the evolution of artificial intelligence technology, applying AI to analyze the vast amount of data from the gut microbiome indicates the potential that artificial intelligence and computational biology hold in transforming medical diagnostics and personalized medicine.
Methods: We conducted metagenomic sequencing on stool samples from 42 patients diagnosed with glioma after operation and 30 non-intracranial tumor patients and developed a Gradient Boosting Machine (GBM) machine learning model to predict the glioma patients based on the gut microbiome data.
Medicine (Baltimore)
September 2025
Department of Orthopedic Surgery, Wenzhou TCM Hospital of Zhejiang Chinese Medical University, Wenzhou, China.
The purpose of this study was to investigate potential therapeutic targets for osteosarcoma (OS) and offer hints regarding genetic factors for OS treatment using a bioinformatics method. This study processed 3 OS datasets from the gene expression omnibus database using R software, screening for differentially expressed genes (DEGs). After enrichment analysis, based on expression quantitative trait loci data and the genome-wide association study data of OS, Mendelian randomization analysis was used to screen the genes closely related to OS disease, which intersect with DEGs to obtain co-expressed genes, validation datasets were employed to verify the results.
View Article and Find Full Text PDFLiver Int
October 2025
Division of Gastroenterology and Hepatology, Department of Medicine, The Institute for Bioelectronic Medicine, Feinstein Institutes for Medical Research & Cold Spring Harbor Laboratory, Northwell Health, Manhasset, New York, USA.
Background: Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related deaths, primarily due to late-stage diagnosis. In this multicenter study, our goal is to identify functional biomarkers that stratify the risk of HCC in patients with cirrhosis (CP) for early diagnosis.
Methods: Five thousand and eight serum proteins (Somascan) were analysed in Cohort A (477 CP, including 125 HCC).