Pathology

Reconfigurable ferroelectric chiral nanostructures enable fast-switchable optical spatial differentiation.

Analog spatial differentiation is an emerging computational paradigm. By virtue of high speed and low-power consumption, optical method plays an important role in data compression, microscopy and computer vision. However, most developed optical differentiators are static and lack the reconfigurability of differentiation functions. Herein, we propose a reconfigurable space-variant ferroelectric chi...

Ensemble machine learning for predicting flexural capacity of FRCM-strengthened RC beams.

Fabric reinforced cementitious matrix (FRCM) composites are progressively applied to strengthen reinforced concrete (RC) members because they offer improved compatibility, durability and fire resistance compared with epoxy-bonded fibre reinforced polymer (FRP) systems. However, predicting the ultimate flexural capacity of FRCM-strengthened beams remains challenging due to the complex interaction o...

Heterologous expression and characterization of Rhodococcus opacus R7 laccase-like multicopper oxidase (LMCO1) enzyme for polyethylene biodegradation.

The production rate of Polyethylene (PE) has increased to a concerning level, necessitating effective strategies to reduce its environmental impacts. ...

LumbarSR: A Paired Clinical CT and Photon-Counting Micro-CT Dataset for Human Lumbar Vertebrae.

Low back pain affects hundreds of millions of people and is associated with degenerative changes in the lumbar spine. Trabecular bone microarchitectur...

Annotated digital image correlation displacement fields from fatigue crack growth experiments on aluminium alloys.

We present a curated dataset of planar displacement fields from eight fatigue crack growth experiments obtained via full-field digital image correlati...

CT-based radiomics as a non-invasive virtual biopsy for high PD-L1 expression prediction in non-small cell lung cancer.

PURPOSE: Non-small cell lung cancer (NSCLC) remains a major clinical challenge, with Programmed death-ligand 1 (PD-L1) expression serving as a crucial...

Identification and prognostic analysis of genes related to CTNNB1 mutations in hepatocellular carcinoma.

BACKGROUND: Mutations in CTNNB1 are recognized oncogenic drivers of hepatocellular carcinoma (HCC); however, the downstream effector molecules and the...

Integrated single-cell RNA sequencing and Bulk-RNA technologies reveal the immunological characteristics of lactylation related-genes in glioblastoma.

OBJECTIVE: Glioblastoma (GBM) is the most aggressive type of intracranial malignant tumor, known for its extremely poor prognosis. Lactylation, a newl...

Corneal nerve regeneration: treatments and monitoring approaches.

BACKGROUND: Diagnostics and therapeutics for corneal nerve pathologies are rapidly evolving, with continual advancements in imaging, laser, machine le...

[Colorectal cancer diagnosis method based on dynamic gland-aware and tissue soft-clustering].

In colorectal cancer histopathology, the collaborative perception of microscopic and salient lesions is critical for effective diagnosis and improved ...

Integrating machine learning with histopathological, immunohistochemical, and PET parameters in the study of invasive breast carcinoma, no special type.

BACKGROUND: This study investigates the relationship between histopathological (HP) features, immunohistochemical (IHC) markers, 18F- FDG PET/CT param...

Review Article: Advances in the Diagnosis of Dysplasia in Barrett's Oesophagus.

BACKGROUND: Barrett's oesophagus (BE), the precursor to oesophageal adenocarcinoma, progresses through a stepwise dysplastic sequence. Accurate dyspla...

SegJointGene: joint cell segmentation and spatial gene prioritization by information entropy guided convolutional neural networks.

MOTIVATION: Spatial sequencing technologies enable the single-cell-level study of molecular organization in tissues. Revealing such spatial patterns r...

Heterogeneity Analyzed by CT-Based Habitat Analysis for Clinical Management of Cancers: A Narrative Review.

Tumors are highly heterogeneous, and whole-lesion radiomics analysis is a popular method for extracting texture features that reflect this heterogenei...

AI-driven discovery of GPNMB CAR T cells as a multi-cancer therapy.

Chimeric antigen receptor (CAR) T cells have demonstrated curative potential in hematologic cancers and increasing efficacy in solid tumors and non-ma...

Development of a LASSO-based machine learning model for relapse prediction in lupus nephritis.

OBJECTIVE: To identify the predictors of renal relapse in patients with lupus nephritis (LN) and develop a predictive model. METHODS: The patients wit...

IL4Rα blockade inhibits proliferation of malignant lymphocytes and the immunosuppressive tumor microenvironment of mycosis fungoides.

BACKGROUND: Limited therapeutic options are available for patients with advanced-stage mycosis fungoides (MF), and the 5-year survival rate is 25%. Du...

Diagnosis of Small Focal Liver Lesions (≤2 cm): A Deep Learning Approach Based on B-Mode Ultrasound and Contrast-Enhanced Ultrasound.

BACKGROUND: To develop and validate a deep learning (DL) model based on feature fusion with B-mode ultrasound (BMUS) and contrast enhanced ultrasound ...

Spatially identifying regions of tumor recurrence in patients with suspected recurrent glioma using physiologic MRI and machine learning.

Despite prior success in classifying recurrent glioma noninvasively with multi-parametric MRI and AI, clinical applicability has yet to be demonstrate...

Oral squamous cell carcinoma diagnosis: an interpretable deep learning approach using multi-scale pathological images.

BACKGROUND: Diagnosis of oral squamous cell carcinoma (OSCC) currently relies heavily on the subjective experience of pathologists. This process is ti...