Myeloma

msCNN-PLM-FAD: Enhanced predicting FAD binding sites by using protein language representation combined with multiple separable windows convolutional neural networks.

The FAD binding sites classification problem is crucial because it is directly related to many diseases, such as flavoprotein-associated diseases, developmental disorders, digestive and lipid metabolism abnormalities, anemia, cancer, cardiovascular diseases, and neurological diseases. Researchers have conducted numerous studies to classify FAD binding sites, achieving varying levels of effectivene...

A peptide immunomodulator activates MST1 to expand and stabilize murine and human regulatory T cells for immune tolerance.

The expansion and potentiation of regulatory T cells (Treg cells) offer an appealing approach for achieving immune tolerance and controlling overactive immune responses across a range of diseases. Current therapeutic approaches to expanding and improving function of Treg cells have predominantly relied on protein-based biologics, such as recombinant interleukin-2 (IL-2); in contrast, peptide-based...

Regional brain age is decreased in children with sickle cell anemia.

DeepBrainNet, a machine learning tool, uses magnetic resonance imaging (MRI) to predict an individual's brain age, allowing calculation of the brain a...

Regional brain age is decreased in children with sickle cell anemia.

DeepBrainNet, a machine learning tool, uses magnetic resonance imaging (MRI) to predict an individual's brain age, allowing calculation of the brain a...

Non-invasive differentiation of light chain amyloidosis and multiple myeloma based on Raman spectroscopy analysis using one-dimensional convolutional neural networks.

Light chain amyloidosis (AL) and multiple myeloma (MM) are interrelated plasma cell disorders characterized by malignant proliferation, yet they demon...

Artificial Intelligence-Based Analysis of Central Nervous System Vasculopathy in Pediatric Sickle Cell Anemia.

In children with sickle cell anemia (SCA), central nervous system (CNS) complications such as chronic vasculopathy, silent cerebral infarcts, and over...

Assessment of Predictive Factors That Shorten Duration of Treatment in Patients With Multiple Myeloma Using AI: Real-World Longitudinal Study Using Data From Medical Data Vision Claims Database.

BACKGROUND: With the availability of newer therapies, the duration of therapy (DoT) shortens with each increasing line of treatment in Japanese patien...

Novel Systemic Associations of Idiopathic Epiretinal Membrane Identified via Machine Learning.

PURPOSE: To discover novel systemic associations that may lead to idiopathic epiretinal membrane (iERM) using interpretable machine learning models. D...

Lesion-level dual-tracer PET biomarkers predict prognosis in multiple myeloma treated with CXCR4-directed radiopharmaceutical therapy.

BACKGROUND: C-X-C motif chemokine receptor 4 (CXCR4)-directed radiopharmaceutical therapy (RPT) represents a promising option for hematologic malignan...

An odyssey of monoclonal gammopathies: focusing on precursors and the progression from MGUS and SMM to multiple Myeloma, with a brief overview of novel therapeutic strategies.

Monoclonal gammopathies span a continuum from monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM) to overt...

Growth differentiation factor 15 promotes the malignant progression of multiple myeloma via activation of PI3K/Akt/NF-κB signaling pathway.

Spatiotemporal dynamics and multiple driving factors of antimicrobial resistance in China during the COVID-19 pandemic (2019-2023): a provincial panel data analysis.

Antimicrobial resistance (AMR) poses a critical and growing global health threat, directly causing millions of deaths, with China bearing a significan...

TrkA abundance is increased in cutaneous nerves in bortezomib-induced neuropathy.

Tropomyosin receptor kinase A (TrkA), a high-affinity receptor for nerve growth factor (NGF), is implicated in nociception and local angiogenesis. We ...

Predicting adverse events for risk stratification of chemotherapy based stem cell mobilization in multiple myeloma.

Autologous stem-cell transplantation is a fundamental therapy for multiple myeloma. Although inpatient chemo-based stem-cell mobilization (SCM) is sta...

Multi-omics and machine learning-based profiling of severity signatures in Mycoplasma pneumoniae infection in children.

Mycoplasma pneumoniae pneumonia (MPP) is a common respiratory infection in children; however, the mechanisms driving its progression to severe disease...

Machine learning mortality prediction model for cyclosporine therapy in pediatric aplastic anemia.

The outcomes of children with aplastic anemia receiving cyclosporine monotherapy vary significantly in terms of mortality risk; therefore, a prognosti...

A deep state-space analysis framework for cancer patient latent state estimation and classification from EHR time-series data.

Advancements in deep learning technologies and an increase in medical data have enhanced the accuracy of disease diagnosis and treatment strategies. N...

Tomek links-based SMOTE method for class imbalance in blood cell classification with dual path sliding window attention model.

Medical image processing has transformed the Complete Blood Count (CBC) analysis to enhance diagnostic accuracy and to detect diseases such as neurode...

Prediction of myeloid malignant cells in Fanconi anemia using machine learning.

Fanconi anemia (FA) is an inherited bone marrow failure syndrome with cancer predisposition. Most FA patients develop aplastic anemia during childhood...

The effect of air pollution and household environmental indicators on anemia status among under-five children in low-middle income countries: exploring potential machine learning applications on demographic and health surveys.

Exposure to air pollution has been associated with anemia in children, but little effort has been made in low- and middle-income countries (LMICs) in ...