Oncology/Hematology

Lycopene-rich extract from red guava (Psidium guajava L.) displays cytotoxic effect against human breast adenocarcinoma cell line MCF-7 via an apoptotic-like pathway.

This study investigated a lycopene-rich extract from red guava (LEG) for its chemical composition using spectrophotometry, mass spectrometry, attenuated total reflectance-fourier transform infrared spectroscopy (ATR-FTIR), and computational studies. The cytotoxic activity of LEG and the underlying mechanism was studied in human breast adenocarcinoma cells (MCF-7), murine fibroblast cells (NIH-3T3)...

Parenchyma-sparing hepatectomy (PSH) versus non-PSH for bilobar liver metastases of colorectal cancer.

BACKGROUND: Preoperative interventions have increased the resectability of colorectal cancer (CRC) liver metastases. This retrospective study compares outcomes after liver resection for bilobar CRC metastases between patients who underwent parenchyma-sparing hepatectomy (PSH), i.e., segmentectomies and smaller resections on both lobes, and those treated with non-PSH, i.e., hemihepatectomy plus any...

Open source machine-learning algorithms for the prediction of optimal cancer drug therapies.

Precision medicine is a rapidly growing area of modern medical science and open source machine-learning codes promise to be a critical component for t...

First Ever Use of Proton Stereotactic Body Radiation Therapy Delivered with Curative Intent to Bilateral Synchronous Primary Renal Cell Carcinomas.

Limited therapeutic options exist for inoperable bilateral kidney tumors. We report the first ever use of proton therapy to treat primary renal cell c...

Predicting pathogenic genes for primary myelofibrosis based on a system‑network approach.

The aim of the present study was to predict pathogenic genes for primary myelofibrosis (PMF) using a system‑network approach by combining protein‑prot...

Synthesis of poly(1,2-glycerol carbonate)-paclitaxel conjugates and their utility as a single high-dose replacement for multi-dose treatment regimens in peritoneal cancer.

Current chemotherapeutic dosing strategies are limited by the toxicity of anticancer agents and therefore rely on multiple low-dose administrations. A...

High-Risk Breast Lesions: A Machine Learning Model to Predict Pathologic Upgrade and Reduce Unnecessary Surgical Excision.

Purpose To develop a machine learning model that allows high-risk breast lesions (HRLs) diagnosed with image-guided needle biopsy that require surgica...

Co-stimulation of the fc receptor and interleukin-12 receptor on human natural killer cells leads to increased expression of cd25.

Natural killer (NK) cells serve a critical role in the immune response against microbes and developing tumors. We have demonstrated that NK cells prod...

Design and application of tumor prediction model based on statistical method^.

Two prediction models for tumor prediction based on logistic regression and BP neural network were proposed in this paper; a sensitivity analysis of r...

Cervical cancer histology image identification method based on texture and lesion area features.

The issue of an automated approach for detecting cervical cancer is proposed to improve the accuracy of recognition. Firstly, the cervical cancer hist...

Neutrophil gelatinase-associated lipocalin level is a prognostic factor for survival in rat and human chronic liver diseases.

Chronic liver disease patients often have complications, such as hepatocellular carcinoma (HCC) and acute bacterial infection. Model for end-stage liv...

A novel machine learning approach reveals latent vascular phenotypes predictive of renal cancer outcome.

Gene expression signatures are commonly used as predictive biomarkers, but do not capture structural features within the tissue architecture. Here we ...

SkipCPP-Pred: an improved and promising sequence-based predictor for predicting cell-penetrating peptides.

BACKGROUND: Cell-penetrating peptides (CPPs) are short peptides (5-30 amino acids) that can enter almost any cell without significant damage. On accou...

Application of Deep Learning in Automated Analysis of Molecular Images in Cancer: A Survey.

Molecular imaging enables the visualization and quantitative analysis of the alterations of biological procedures at molecular and/or cellular level, ...

Photoresponsive Block Copolymer Prodrug Nanoparticles as Delivery Vehicle for Single and Dual Anticancer Drugs.

In recent decades, drug delivery systems (DDSs) based on polymer nanoparticles have been explored due to their potential to deliver drugs with poor wa...

Outcome and validation of a new clinically based staging system for predicting survival of perihilar cholangiocarcinoma patients.

BACKGROUND AND AIM: Currently available staging systems for cholangiocarcinoma (CCA) are not applicable to patients with unresectable stage. A new cli...

A deep convolutional neural network-based automatic delineation strategy for multiple brain metastases stereotactic radiosurgery.

Accurate and automatic brain metastases target delineation is a key step for efficient and effective stereotactic radiosurgery (SRS) treatment plannin...

Deep Learning-Based Multi-Omics Integration Robustly Predicts Survival in Liver Cancer.

Identifying robust survival subgroups of hepatocellular carcinoma (HCC) will significantly improve patient care. Currently, endeavor of integrating mu...

Radiomics in Brain Tumor: Image Assessment, Quantitative Feature Descriptors, and Machine-Learning Approaches.

Radiomics describes a broad set of computational methods that extract quantitative features from radiographic images. The resulting features can be us...

Identification of potentially oncogenic alterations from tumor-only samples reveals Fanconi anemia pathway mutations in bladder carcinomas.

Cancer is caused by germline and somatic mutations, which can share biological features such as amino acid change. However, integrated germline and so...