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Molecular Targeted Therapy

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Inside a Metastatic Fracture: Molecular Bases and New Potential Therapeutic Targets.

Cancer medicine
INTRODUCTION: Bone metastases and pathological fractures significantly impact the prognosis and quality of life in cancer patients. However, clinical and radiological features alone have been shown to fail to predict skeletal related events of a bone...

Identification and validation of interferon-stimulated gene 15 as a biomarker for dermatomyositis by integrated bioinformatics analysis and machine learning.

Frontiers in immunology
BACKGROUND: Dermatomyositis (DM) is an autoimmune disease that primarily affects the skin and muscles. It can lead to increased mortality, particularly when patients develop associated malignancies or experience fatal complications such as pulmonary ...

PD-1 Targeted Antibody Discovery Using AI Protein Diffusion.

Technology in cancer research & treatment
The programmed cell death protein 1 (PD-1, CD279) is an important therapeutic target in many oncological diseases. This checkpoint protein inhibits T lymphocytes from attacking other cells in the body and thus blocking it improves the clearance of tu...

Artificial intelligence for small molecule anticancer drug discovery.

Expert opinion on drug discovery
INTRODUCTION: The transition from conventional cytotoxic chemotherapy to targeted cancer therapy with small-molecule anticancer drugs has enhanced treatment outcomes. This approach, which now dominates cancer treatment, has its advantages. Despite th...

Four Genes with Seven Targeted Drugs might be Treatment for Diabetic Nephropathy and Acute Coronary Syndrome.

The Tohoku journal of experimental medicine
Diabetes nephropathy (DN) is a main risk factor for acute coronary syndrome (ACS), but the molecular mechanism is unknown. This research used bioinformatics approaches to uncover potential molecular mechanisms and drugs for DN and ACS. GSE142153 and ...

Biologically Enhanced Machine Learning Model to uncover Novel Gene-Drug Targets for Alzheimer's Disease.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Given the complexity and multifactorial nature of Alzheimer's disease, investigating potential drug-gene targets is imperative for developing effective therapies and advancing our understanding of the underlying mechanisms driving the disease. We pre...

Machine learning-based identification and validation of immune-related biomarkers for early diagnosis and targeted therapy in diabetic retinopathy.

Gene
The early diagnosis of diabetic retinopathy (DR) is challenging, highlighting the urgent need to identify new biomarkers. Immune responses play a crucial role in DR, yet there are currently no reports of machine learning (ML) algorithms being utilize...

Deep learning radiopathomics predicts targeted therapy sensitivity in EGFR-mutant lung adenocarcinoma.

Journal of translational medicine
BACKGROUND: Ttyrosine kinase inhibitors (TKIs) represent the standard first-line treatment for patients with epidermal growth factor receptor (EGFR)-mutant lung adenocarcinoma. However, not all patients with EGFR mutations respond to TKIs. This study...