Predicting brain age using Tri-UNet and various MRI scale features.

In the process of human aging, significant age-related changes occur in brain tissue. To assist individuals in assessing the degree of brain aging, screening for disease risks, and further diagnosing age-related diseases, it is crucial to develop an accurate method for predicting brain age. This paper proposes a multi-scale feature fusion method called Tri-UNet based on the U-Net network structure, as well as a brain region information fusion method based on multi-channel input networks.

Preparation of AlTi-AlO/Al Inoculant and Its Inoculation Effect on Al-Cu-Mn Alloy.

The grain size plays a pivotal role in determining the properties of the alloy. The grain size can be significantly decreased by adding inoculants. Aiming to address the shortcomings of existing inoculants, the AlTi-AlO/Al inoculant was successfully prepared using Al-Ti master alloy and AlO whiskers as raw materials.

The value of machine learning based radiomics model in preoperative detection of perineural invasion in gastric cancer: a two-center study.

Purpose: To establish and validate a machine learning based radiomics model for detection of perineural invasion (PNI) in gastric cancer (GC).

Methods: This retrospective study included a total of 955 patients with GC selected from two centers; they were separated into training (n=603), internal testing (n=259), and external testing (n=93) sets. Radiomic features were derived from three phases of contrast-enhanced computed tomography (CECT) scan images.

A CT-based radiomics signature for prediction of HER2 overexpression and treatment efficacy of trastuzumab in advanced gastric cancer.

Background: Accurate evaluation of human epidermal growth factor receptor 2 (HER2) status is very important for appropriate management of advanced gastric cancer (AGC) patients. In this study, we aimed to develop and validate a computed tomography (CT)-based radiomics signature for preoperative prediction of HER2 overexpression and treatment efficacy of trastuzumab in AGC.

Methods: We retrospectively enrolled 536 consecutive AGC patients (median age, 59 years; interquartile range, 52-65 years; 377 male, 159 female) and separated them into a training set (n=357) and a testing set (n=179).

Multifunctional nanoprobes combined with radiotherapy and hypoxia-activated therapy synergistically improve antitumor efficacy.

The presence of hypoxia in tumors is characteristic of most solid tumors and it promotes not only tumor angiogenesis but also tumor cell invasion and metastasis. It also results in resistance of tumor tissue to radiation, leading to poor outcomes of tumor radiotherapy. Therefore, to address this conundrum, highly selective gold nanoclusters were prepared as fluorescent imaging agents and radiosensitizers and then loaded with tumor hypoxia-activated prodrugs to prepare nanoprobes which synergistically improved the anti-tumor efficacy by combining radiotherapy and hypoxia-activated therapy.

A multiphase contrast-enhanced CT radiomics model for prediction of human epidermal growth factor receptor 2 status in advanced gastric cancer.

Accurate evaluation of human epidermal growth factor receptor 2 (HER2) status is of great importance for appropriate management of advanced gastric cancer (AGC) patients. This study aims to develop and validate a CT-based radiomics model for prediction of HER2 overexpression in AGC. Seven hundred and forty-five consecutive AGC patients (median age, 59 years; interquartile range, 52-66 years; 515 male and 230 female) were enrolled and separated into training set ( = 521) and testing set ( = 224) in this retrospective study.

A CT-based Radiomics Model for Prediction of Lymph Node Metastasis in Early Stage Gastric Cancer.

Rationale And Objectives: To develop and validate a CT-based radiomics model for preoperative prediction of lymph node metastasis (LNM) in early stage gastric cancer (EGC).

Materials And Methods: Four hundred and sixty-three consecutive EGC patients were enrolled in this retrospective study. Radiomics features were extracted from portal venous phase CT scans.

A radiomics-based model for prediction of lymph node metastasis in gastric cancer.

Purpose: To develop and validate a radiomics-based model for preoperative prediction of lymph node metastasis (LNM) in gastric cancer (GC).

Method: A total of 768 GC patients were enrolled in this retrospective study. Radiomics features were extracted from portal venous phase computed tomography (CT) scans.

A CT-based radiomics signature for evaluating tumor infiltrating Treg cells and outcome prediction of gastric cancer.

Background: Tumor infiltrating regulatory T (TITreg) cells are highly infiltrated in gastric cancer (GC) and associated with worse prognosis of GC patients. We aim to develop and validate a radiomics signature for evaluation of TITreg cells and outcome prediction of GC patients.

Methods: A total of 165 GC patients from three independent cohorts were enrolled in this retrospective study.

A seven long-noncoding RNA signature predicts prognosis of lung squamous cell carcinoma.

This study profiled differentially expressed long noncoding RNAs (lncRNAs) in lung squamous cell carcinoma (LSCC) to predict LSCC overall survival (OS) using The Cancer Genome Atlas data. The RNA-seq and clinical dataset of 475 LSCC patients was retrieved from The Cancer Genome Atlas database and statistically analyzed. There were 67 upregulated and 32 downregulated lncRNAs in LSCCs and 12 lncRNAs associated with OS.

T-cell receptor gene therapy targeting melanoma-associated antigen-A4 by silencing of endogenous TCR inhibits tumor growth in mice and human.

Genetically engineered T cells expressing a T-cell receptor (TCR) are powerful tools for cancer treatment and have shown significant clinical effects in sarcoma patients. However, mismatch of the introduced TCR α/β chains with endogenous TCR may impair the expression of transduced TCR, resulting in an insufficient antitumor capacity of modified T cells. Here, we report the development of immunotherapy using human lymphocytes transduced with a codon-optimized melanoma-associated antigen (MAGE)-A4 and HLA-A*2402-restricted TCR, which specifically downregulate endogenous TCR by small interfering RNA (si-TCR).

Identification of hub genes with prognostic values in gastric cancer by bioinformatics analysis.

Background: Gastric cancer (GC) is a prevalent malignant cancer of digestive system. To identify key genes in GC, mRNA microarray GSE27342, GSE29272, and GSE33335 were downloaded from GEO database.

Methods: Differentially expressed genes (DEGs) were obtained using GEO2R.

A novel microRNA signature predicts survival in stomach adenocarcinoma.

Recent microRNA (miRNA) expression profiling studies suggest the clinical use of miRNAs as potential prognostic biomarkers in various malignancies. In this study, aiming to identify microRNAs with prognostic value for overall survival (OS) in stomach adenocarcinoma (STAD) patients, we analyzed the miRNA expression profiles and the associated clinical characteristics in 380 STAD samples from The Cancer Genome Atlas (TCGA) dataset. An eight-miRNA signature for predicting OS in STAD patients was identified and self-validated by survival analysis and semi-supervised principal components method.

Identification of a seven-miRNA signature as prognostic biomarker for lung squamous cell carcinoma.

Background: Specific biomarkers for outcome prediction of lung squamous cell carcinoma (LUSC) are still lacking. This study assessed the prognostic value of differentially expressed miRNAs of LUSC patients.

Results: Twelve of the 133 most significantly altered miRNAs were associated with overall survival (OS) across different clinical subclasses of the Cancer Genome Atlas (TCGA) LUSC cohort.

Plasma miR-324-3p and miR-1285 as diagnostic and prognostic biomarkers for early stage lung squamous cell carcinoma.

Background: Specific biomarkers for early detection and outcome prediction of lung squamous cell carcinoma (LSCC) are still lacking. This study assessed the differentially expressed miRNAs as potential biomarkers for early stage LSCC.

Results: Base on the results of multi-phase study, we found that miR-324-3p was significantly up-regulated, whereas mir-1285 was significantly down-regulated in plasma of stage I LSCC patients compared to healthy controls.

Identification of a three-miRNA signature as a blood-borne diagnostic marker for early diagnosis of lung adenocarcinoma.

Background: The subtypes of NSCLC have unique characteristics of pathogenic mechanism and responses to targeted therapies. Thus, non-invasive markers for diagnosis of different subtypes of NSCLC at early stage are needed.

Results: Based on the results from the screening and validation process, 3 miRNAs (miR-532, miR-628-3p and miR-425-3p) were found to display significantly different expression levels in early-stage lung adenocarcinoma, as compared to those in healthy controls.

The hOGG1 Ser326Cys polymorphism contributes to digestive system cancer susceptibility: evidence from 48 case-control studies.

The Ser326Cys polymorphism in the human 8-oxogunaine DNA glycosylase (hOGG1) gene had been implicated in cancer susceptibility. Studies investigating the associations between the Ser326Cys polymorphism and digestion cancer susceptibility showed conflicting results. Therefore, a meta-analysis was performed to derive a more precise estimation of the relationship.

Diagnostic and prognostic value of circulating miR-21 for cancer: a systematic review and meta-analysis.

Background: MicroRNAs (miRNAs) have been reported to be aberrantly expressed in patients with cancer. Many studies have shown that circulating miRNAs could play potential roles as diagnostic and prognostic biomarkers of cancers. The aim of this meta-analysis is to summarize the role of circulating miR-21 as a biomarker in patients with a variety of carcinomas.