Leukemia

Software-based de-filtering restores quantitative accuracy in Clarity2D-enhanced whole-body bone scintigraphy.

OBJECTIVE: To determine whether software-based de-filtering can restore the quantitative accuracy of the bone scan index (BSI) and the number of hot spots (HSn) in whole-body scintigraphy images degraded by the Clarity2D noise-reduction filter. METHODS: In this IRB-approved retrospective study, 101 adults (mean age ± SD: 67 ± 13 years) who underwent 99mTc-HMDP whole-body scintigraphy on a cadmium-...

Machine learning-assisted prognosis of multiple myeloma side population cells via SRGs and OCLR stemness index.

BACKGROUND AND OBJECTIVE: Relapse in Multiple Myeloma, driven by therapy-resistant cancer stem cells, necessitates the development of more specific and accurate prognostic models. Existing stemness indices often lack specificity for the unique biology of Multiple Myeloma. This study aimed to develop, validate, and optimize a novel prognostic gene signature derived from Side Population cells, a wel...

Decoding Senescence-Driven Heterogeneity in Early-Onset Colorectal Cancer for Prognostic and Therapeutic Stratification.

Early-onset colorectal cancer (EOCRC), diagnosed in patients under 50, is particularly aggressive, yet lacks targeted therapeutic strategies. This stu...

Polyploid giant cancer cells: A novel target in future cancer therapy.

Under intense therapeutic stress-including chemotherapy, radiotherapy, and targeted therapies-tumor cells can undergo ploidy reprogramming to generate...

AI-Enabled Early Detection of Chemo-Induced Cardiotoxicity Patterns Using ECG Time Series Data: A Simulated Oncology Framework.

OBJECTIVES: Chemotherapy-induced cardiotoxicity is still a major clinical problem, usually appearing subclinically before structural or symptomatic ca...

Chemotherapy-Sparing Strategies in Follicular Lymphoma: Emerging Targeted and Immune-Based Approaches.

Follicular lymphoma (FL), traditionally considered an indolent yet incurable malignancy, is experiencing a substantial evolution in its therapeutic la...

Machine Learning-Based Prediction Model for Alveolar Bone Defect Risk Following Orthodontic Treatment.

OBJECTIVES: Alveolar bone defects, such as fenestration and dehiscence, induced by orthodontic treatment represent significant complications that can ...

Visceral Adipose Tissue Alters Podometrics and Renal Compensation After Uninephrectomy.

INTRODUCTION: Obesity is an established risk factor for chronic kidney disease (CKD). However, excess visceral adipose tissue (VAT) termed visceral ob...

Integrating global burden of disease analysis and single-cell omics identifies ANTXR2 as a potential diagnostic biomarker for AML in China.

BACKGROUND: The epidemiological characteristics of acute myeloid leukemia (AML) in China, including long-term trends and reliable diagnostic biomarker...

Time-resolved prediction of dental implant biomechanics through integration of finite element analysis, osseointegration dynamics, and deep learning.

BACKGROUND: Dental implant longevity depends on the complex interaction between mechanical stability and biological osseointegration. While finite ele...

Machine learning-guided repurposing of FDA-approved quinolones as dual cholinesterase inhibitors: A multi-level docking, molecular dynamics, DFT, and SHAP-based analysis.

Alzheimer's disease (AD) involves progressive cholinergic degeneration, with acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) playing key ...

Modulating tumor mechanics and vascular barriers to enhance chemotherapy efficacy in pancreatic tumors and melanoma.

Pancreatic ductal adenocarcinoma (PDAC) is characterized by a dense stroma and dysfunctional vasculature, limiting drug delivery and immune infiltrati...

Integrative bioinformatics analysis reveals that microplastics promote chronic rhinosinusitis with nasal polyps through NOXO1-mediated oxidative stress and myoepithelial cell reprogramming.

Chronic rhinosinusitis with nasal polyps (CRSwNP) is a complex inflammatory disease whose environmental pathogenic factors remain unclear. Microplasti...

Predicting skeletal age from HR-pQCT imaging.

INTRODUCTION: High-resolution peripheral quantitative computed tomography (HR-pQCT) provides detailed bone microarchitecture assessments, but the inte...

Coronary Artery Brightness on Echocardiography as a Novel Marker in Kawasaki Disease　- Machine Learning-Based Cluster Analysis.

BACKGROUND: Coronary artery brightness (CAB) on echocardiography has been observed during the acute phase of Kawasaki disease (KD), but its clinical r...

AI-Driven CT-MRI Image Fusion and Segmentation for Automatic Preoperative Planning of ACL Reconstruction: Development and Application.

BACKGROUND: The goals of this study were to develop an artificial intelligence (AI)-driven automated preoperative planning system for anterior cruciat...

Mri-based habitat and peritumoral radiomics for predicting the proliferative activity of stromal cells in giant cell tumor of bone.

PURPOSE: This study aims to explore the feasibility of MRI-based habitat and peritumoral radiomics for predicting the proliferative activity of stroma...

Prediction of Postherpetic Neuralgia in Patients with Acute and Subacute Herpetic Neuralgia Using Structural Magnetic Resonance Imaging: A Retrospective Study.

INTRODUCTION: This study integrated structural magnetic resonance imaging (sMRI) of the brain with clinical characteristics to identify the "vulnerabl...

The global epidemiology of acute myeloid leukaemia.

Acute myeloid leukaemia (AML) is an aggressive haematological malignancy with an incidence that increases with age and varies widely across regions ow...

Developing and Validating a Prediction Model for the Severe Pain-Fatigue-Sleep Disturbance Symptom Cluster in Patients with Lung Cancer Following Chemotherapy: A Machine Learning Analysis.

OBJECTIVES: Pain-fatigue-sleep disturbance symptom (PFS) cluster is the most common symptom cluster in patients with lung cancer following chemotherap...