Pathology

Correlation between oral disease and neurodegenerative disorders: Role of biological proteins for the modulation of oral-brain axis and gut-brain axis.

Biological proteins play a crucial role at the intersection of oral health and neuroscience, offering promising opportunities for improved diagnosis, prevention, and treatment. This review highlights the molecular, inflammatory, and biochemical pathways linking oral diseases, particularly periodontal disease and microbial dysbiosis, with neurodegenerative disorders such as Alzheimer's and Parkinso...

Large-scale DNA organization analysis of primary breast cancers for prediction of axillary lymph node metastases.

Breast cancer is the leading cause of cancer-related deaths among women worldwide. It is standard practice for patients to undergo a sentinel lymph node biopsy (SLNB) with breast surgery for staging. However, more than 60% of patients with primary operable breast cancers do not have axillary lymph node metastases. Hence, most patients risk complications from SLNB, but do not benefit. There has bee...

Cervical cancer cell prediction and detection with high test accuracy based on a reliable automated system.

Cervical cancer ranks as the fourth most prevalent cancer among women worldwide. The increasing incidence and mortality rates are largely attributed t...

MIL-Adapter: Coupling multiple instance learning and vision-language adapters for few-shot slide-level classification.

Contrastive language-image pretraining has greatly enhanced visual representation learning and enabled zero-shot classification. Vision-language langu...

His-MMDM: Multi-Domain and Multi-Omics Translation of Histopathological Images with Diffusion Models.

Generative AI (GenAI) has advanced computational pathology through various image translation models. These models synthesize histopathological images ...

Hierarchical image pyramid transformer framework for automated breast cancer molecular subtyping using tissue microarrays.

The heterogeneity of breast cancer at molecular and histological levels poses significant challenges for precise diagnosis and treatment. Current mole...

Bridging Microscopic Dynamics and Macroscopic Fate: A Molecular Dynamics-Machine Learning Approach for Predicting PFAS Solid-Liquid Distribution in Soils and Sediments.

Per- and polyfluoroalkyl substances (PFAS) are persistent global contaminants, posing challenges to predicting their environmental fate. The solid-liq...

Angioimmunoblastic T-cell lymphoma with lymphomatous effusion: Diagnostic challenges and cytology-based approaches.

Angioimmunoblastic T-cell lymphoma (AITL) is an aggressive peripheral T-cell lymphoma with a poor prognosis. Lymphomatous serous effusion, defined as ...

Deep learning outperformed radiomics based on MRI in the differentiation of sinonasal small round cell and non-small round cell malignant tumors.

OBJECTIVE: Differentiating sinonasal small round cell malignant tumors (SRCMTs) from non-SRCMTs is challenging due to overlapping MRI features. This s...

[Transformation of gastrointestinal surgery diagnosis and treatment models].

In recent years, with the rapid development of medical device and biopharmaceutical technologies, the treatment model of gastric cancer surgery has be...

[Trends in the development of clinical diagnosis and treatment models for gastrointestinal tumor surgery in the artificial intelligence era].

Gastrointestinal tumors represent a significant global public health challenge, characterized by high incidence and mortality, which reflect the urgen...

[A new paradigm for precision diagnosis and treatment of colorectal cancer in the era of artificial intelligence--From foundation models to multi-agent collaboration].

The high heterogeneity of colorectal cancer poses significant challenges to clinical precision diagnosis and treatment. In recent years, artificial in...

[Diagnosis and treatment of colorectal cancer in the era of artificial intelligence: review and prospect].

In recent years, artificial intelligence (AI) has achieved groundbreaking progress in the field of medicine, particularly in the diagnosis and treatme...

Automatic and accurate auxiliary detection of lung cancer pathological classification based on novel lightweight deep learning model.

BACKGROUND: Lung cancer is one of the major cancers worldwide, and rapid, accurate diagnosis is crucial for subsequent treatment and management. Curre...

Breast cancer frontiers: mapping molecular signals, intelligent diagnostics, and adaptive therapies.

Breast cancer continues to be a significant worldwide health concern, requiring ongoing improvements in early detection, therapeutic approaches, and c...

Immunohistochemical biomarker-associated radiomics for classifying thymic epithelial tumors: a multicenter retrospective study.

The subtle imaging features of thymic epithelial tumors (TETs), which comprise multiple pathological subtypes of thymoma and thymic carcinoma, are of ...

Predicting kidney graft survival with a machine learning model based on for-cause biopsy transcriptomics.

Kidney transplantation significantly improves outcomes in end-stage renal disease, however, long-term graft survival remains suboptimal. Traditional p...

Research on the molecular mechanism of celastrol targeting CTNNB1/STAT3 to inhibit uveal melanoma based on network pharmacology and multi-omics analysis.

Uveal melanoma (UM) is among the most prevalent intraocular malignant tumors worldwide. Celastrol exhibits broad-spectrum anticancer properties; howev...

Deep learning for malignancy and tumor origin prediction using cytology or histopathology whole slide images.

Pleural and ascitic cytology is essential for diagnosing metastatic cancer and predicting tumor origin, yet microscopic observation alone often leads ...

From Tissue Archives to Liquid Biopsy: Transfer Learning for MicroRNA-Based Lung Cancer Diagnosis.

Serum microRNA-based liquid biopsy holds a great application prospect in noninvasive lung cancer diagnosis. However, building an efficient serum-based...