Leukemia

Decoding the diagnostic biomarkers of mitochondrial dysfunction related gene variants in pediatric T cell acute lymphoblastic leukemia.

Mitochondrial dysfunction is crucial in the pathogenesis and drug resistance of pediatric T-cell acute lymphoblastic leukemia (T-ALL), a malignant hematological disorder with unrestrained proliferation of immature T-cells. Therefore, the primary objective of this study is to elucidate the role of mitochondrial dysfunction-related differentially expressed genes (MDRDEGs) in pediatric T-ALL and to e...

Development and validation of an interpretable machine learning model for predicting Philadelphia chromosome-positive acute lymphoblastic leukaemia using clinical and laboratory parameters: a single-centre retrospective study.

OBJECTIVE: To develop and validate a prediction model of Philadelphia chromosome-positive acute lymphoblastic leukaemia (Ph+ALL).

Aptamer-directed siRNA delivery systems for triple-negative breast cancer therapy.

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer characterized by the absence of estrogen, progesterone, and HER2 recept...

Intra-tumor microbiome-based tumor survival indices predict immune interaction and drug sensitivity on pan-cancer scale.

UNLABELLED: Growing research evidence indicates a substantial influence of the intra-tumor microbiome on tumor outcome. However, there is currently no...

Fully automated workflow for designing patient-specific orthopaedic implants: Application to total knee arthroplasty.

Background Osteoarthritis affects about 528 million people worldwide, causing pain and stiffness in the joints. Arthroplasty is commonly performed to ...

Quantum Kernel Learning for Small Dataset Modeling in Semiconductor Fabrication: Application to Ohmic Contact.

Modeling complex semiconductor fabrication processes such as Ohmic contact formation remains challenging due to high-dimensional parameter spaces and ...

Accurate de novo design of high-affinity protein-binding macrocycles using deep learning.

Developing macrocyclic binders to therapeutic proteins typically relies on large-scale screening methods that are resource intensive and provide littl...

A compact encoding of the genome suitable for machine learning prediction of traits and genetic risk scores.

Genotype to phenotype prediction is a central problem in biology and medicine. Machine learning is a natural tool to address this problem. However, a ...

An In-depth overview of artificial intelligence (AI) tool utilization across diverse phases of organ transplantation.

Artificial Intelligence (AI) offers a revolutionary approach to improve decision-making in medicine through the use of advanced computational tools. I...

Machine learning driven dashboard for chronic myeloid leukemia prediction using protein sequences.

The prevalence of Leukaemia, a malignant blood cancer that originates from hematopoietic progenitor cells, is increasing in Southeast Asia, with a wor...

Next-generation cancer therapeutics: unveiling the potential of liposome-based nanoparticles through bioinformatics.

Cancer remains one of the most deadly diseases in the world, requiring constant growth and improvements in therapeutic strategies. Traditional cancer ...

Machine learning-based models for outcome prediction in skull base and spinal chordomas: a systematic review and meta-analysis.

BACKGROUND: Chordomas are primary bone lesions originating from embryonic notochord remnants, most commonly developing along the skull base and spine....

Automated quantitative analysis of peri-articular bone microarchitecture in HR-pQCT knee images.

UNLABELLED: Applying HR-pQCT to image the knee necessitates the development and validation of novel image analysis workflows. Here, we present and val...

Development and validation of an MRI spatiotemporal interaction model for early noninvasive prediction of neoadjuvant chemotherapy response in breast cancer: a multicentre study.

BACKGROUND: The accurate and early evaluation of response to neoadjuvant chemotherapy (NAC) in breast cancer is crucial for optimizing treatment strat...

RNAS-sgRNA: Recurrent Neural Architecture Search for Detection of On-Target Effects in Single Guide RNA.

Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas9 is a leading genomic editing tool, but its effectiveness is limited by conside...

Integrative multi-omics profiling deciphers tumor microenvironment heterogeneity and immunotherapy vulnerabilities in lung neuroendocrine carcinomas.

INTRODUCTION: Lung neuroendocrine carcinomas (Lu-NECs) are rare, highly aggressive lung tumors with poor prognosis and limited therapeutic options. Un...

DeepHeme, a high-performance, generalizable deep ensemble for bone marrow morphometry and hematologic diagnosis.

Cytomorphological analysis of the bone marrow aspirate (BMA) is pivotal for the diagnostic workup of a broad range of hematological disorders. However...

Screening of Biomaterials for Stem Cell Culture Applications.

Stem cells have a considerable role to play in future biomedical breakthroughs due to their therapeutic potential. As stem cells may be studied in a v...

Identification of DSC2 as a Key Biomarker for Induction Chemotherapy Sensitivity in Locally Advanced Laryngeal and Hypopharyngeal Squamous Cell Carcinoma.

Patients with locally advanced laryngeal and hypopharyngeal squamous cell carcinoma (LA-LHSCC) urgently need precise treatment strategies to improve t...

Single-cell sequencing and machine learning reveal the role of dioxin-interacting genes in HCC prognosis and immune microenvironment.

Dioxins are persistent environmental pollutants that bioaccumulate in the food chain, posing significant risks to human health. Despite their low envi...