Leukemia

Improved analytical workflow towards machine learning supported N-glycomics-based biomarker discovery.

The composition and function of glycans are very complex thus manual data interpretation of their structural elucidation is difficult. Capillary electrophoresis is one of the liquid phase separation techniques, which is most frequently used to address these challenging tasks. Combining high-resolution capillary electrophoresis with machine learning-supported data interpretation holds the promise t...

CytoLNCpred-a computational method for predicting cytoplasm associated long non-coding RNAs in 15 cell-lines.

The function of long non-coding RNA (lncRNA) is largely determined by its specific location within a cell. Previous methods have used noisy datasets, including mRNA transcripts in tools intended for lncRNAs, and excluded lncRNAs lacking significant differential localization between the cytoplasm and nucleus. In order to overcome these shortcomings, a method has been developed for predicting cytopl...

Skeletal Muscle Density as a Predictive Marker for Pathologic Complete Response in Triple-Negative Breast Cancer Treated with Neoadjuvant Chemoimmunotherapy.

: The predictive value of muscle-related indicators in triple-negative breast cancer (TNBC) patients undergoing neoadjuvant chemotherapy (NAC) remains...

Epidemiology and survival of patients with primary lymphoma of bone: a large retrospective cohort study.

Primary lymphoma of bone (PLB) is a rare extranodal lymphoma, and its epidemiology and prognosis remain controversial. We conducted a retrospective an...

National Guidelines for Cytoreductive Surgery and Hyperthermic Intraperitoneal Chemotherapy (HIPEC) in Peritoneal Malignancies: A Worldwide Systematic Review and Recommendations of Strength Analysis.

BACKGROUND: National guidelines (GLs) for surgical cytoreduction (CRS) and hyperthermic intraperitoneal chemotherapy (HIPEC) in the management of peri...

Explainable machine learning and feature interpretation to predict survival outcomes in the treatment of lung cancer.

The treatment outcomes of lung cancer are highly variable, and machine learning (ML) models provide valuable insights into how clinical and biochemica...

CDKN1A and EGR1 are key genes for endoplasmic reticulum stress-induced ferroptosis in MASH.

Metabolic dysfunction-associated steatohepatitis (MASH) is a complex liver disease whose pathogenesis involving endoplasmic reticulum (ER) stress and ...

Oral ENPP1 inhibitor designed using generative AI as next generation STING modulator for solid tumors.

Despite the STING-type-I interferon pathway playing a key role in effective anti-tumor immunity, the therapeutic benefit of direct STING agonists appe...

Multiscale analysis and optimal glioma therapeutic candidate discovery using the CANDO platform.

Glioma is a highly malignant brain tumor with limited treatment options. We employed the Computational Analysis of Novel Drug Opportunities (CANDO) pl...

Design, synthesis, and evaluation of triazolo[1,5-a]pyridines as novel and potent α‑glucosidase inhibitors.

α-Glucosidase is a key enzyme responsible for controlling the blood glucose, making a pivotal target in the treatment of type 2 diabetes mellitus. Pre...

AttentionAML: An Attention-based Deep Learning Framework for Accurate Molecular Categorization of Acute Myeloid Leukemia.

Acute myeloid leukemia (AML) is an aggressive hematopoietic malignancy defined by aberrant clonal expansion of abnormal myeloid progenitor cells. Char...

A Machine Learning Method for Predicting Acute Kidney Injury in Patients with Intracranial Hemorrhage.

Intracranial hemorrhage (ICH) is a critical and urgent condition in clinical practice. Recent research has highlighted acute kidney injury (AKI) that ...

Prediction of B/T Subtype and ETV6-RUNX1 Translocation in Pediatric Acute Lymphoblastic Leukemia by Deep Learning Analysis of Giemsa-Stained Whole Slide Images of Bone Marrow Aspirates.

BACKGROUND: Accurate determination of B/T-cell lineage and the presence of the ETV6-RUNX1 translocation is critical for diagnosing acute lymphoblastic...

Establishment of a prognostic model based on ER stress-related cell death genes and proposing a novel combination therapy in acute myeloid leukemia.

BACKGROUND: Acute myeloid leukemia (AML) is a highly heterogeneous malignancy, presenting significant challenges in accurately predicting patient prog...

Applications of machine learning for immunophenotypic measurable residual disease assessment in acute myeloid leukemia.

Immunophenotypic detection and quantification of residual leukemic cells by multiparameter flow cytometry is increasingly adopted in the clinical prac...

Advances of oncolytic vaccinia viruses armed with interleukin in tumor therapy.

Oncolytic vaccinia viruses armed with interleukins represent a promising frontier in tumor therapy. Oncolytic vaccinia viruses express IL-2, IL-10, IL...

External validation of the Oncotype DX breast cancer recurrence score nomogram and development and validation of a novel machine learning-based model to predict postoperative overall survival and guide adjuvant chemotherapy in ER positive, Her-2 negative breast cancer patients: a retrospective cohort study.

BACKGROUND: This study aims to externally validate the performance of the Oncotype DX (ODX) breast cancer (BC) recurrence score nomogram in predicting...

Label-Free and Intelligent Cell Death Recognition Toward Lung Cancer Chemotherapy.

The lack of high-throughput, label-free, and intelligent recognition models for assessing cell death hinders the broad application of cell death analy...

Deep learning-based interpretable prediction of recurrence of diffuse large B-cell lymphoma.

BACKGROUND: The heterogeneous and aggressive nature of diffuse large B-cell lymphoma (DLBCL) presents significant treatment challenges as up to 50% of...

Predicting Treatment Outcomes in Glioblastoma: A Risk Score Model for TMZ Resistance and Immune Checkpoint Inhibition.

Glioblastoma (GBM) presents significant therapeutic challenges due to its invasive nature and resistance to standard chemotherapy, i.e., temozolomide ...