Brain metastasis reirradiation in patients with advanced breast cancer.

The outcome of recurrent brain metastasis is dismal. This study aims to assess the clinical outcomes and toxicity of reirradiation as a salvage treatment for progressive brain metastasis in patients with advanced breast cancer. Between July 2005 and September 2014, the medical records of 56 patients with brain metastasis from breast cancer were retrospectively reviewed.

Cystic brain metastasis is associated with poor prognosis in patients with advanced breast cancer.

Purpose: Brain metastasis (BM) with a cystic component from breast cancer is rare and largely uncharacterized. The purpose of this study was to identify the characteristics of cystic BM in a large cohort of breast cancer patients.

Results: A total of 35 eligible patients with cystic BM and 255 patients with solid BM were analyzed.

Incidence and relapse risk of intracranial metastases within the perihippocampal region in 314 patients with breast cancer.

Purpose: The safe prerequisite of hippocampal-sparing whole brain radiotherapy (HS-WBRT) for patients with breast cancer is unclear. This study investigated the risk and relapse of perihippocampal (PH) metastases in breast cancer.

Methods: Consecutive breast cancer patients with brain metastasis (BM) were reviewed.

Predicting linear B-cell epitopes using amino acid anchoring pair composition.

Background: Accurate identification of linear B-cell epitopes plays an important role in peptide vaccine designs, immunodiagnosis, and antibody productions. Although several prediction methods have been reported, unsatisfied accuracy has limited the broad usages in linear B-cell epitope prediction. Therefore, developing a reliable model with significant improvement on prediction accuracy is highly desirable.

sRNATarBase: a comprehensive database of bacterial sRNA targets verified by experiments.

Bacterial sRNAs are an emerging class of small regulatory RNAs, 40-500 nt in length, which play a variety of important roles in many biological processes through binding to their mRNA or protein targets. A comprehensive database of experimentally confirmed sRNA targets would be helpful in understanding sRNA functions systematically and provide support for developing prediction models. Here we report on such a database--sRNATarBase.

sRNATarget: a web server for prediction of bacterial sRNA targets.

Unlabelled: In bacteria, there exist some small non-coding RNAs (sRNAs) with 40-500 nucleotides in length. Most of them function as posttranscriptional regulation of gene expression through binding to their target mRNAs, in which Hfq protein acts as RNA chaperone. With the increase of identified sRNA genes in the bacterium, prediction of sRNA targets plays a more important role in determining sRNA functions.

Construction of two mathematical models for prediction of bacterial sRNA targets.

Accurate prediction of sRNA targets plays a key role in determining sRNA functions. Here we introduced two mathematical models, sRNATargetNB and sRNATargetSVM, for prediction of sRNA targets using Nai ve Bayes method and support vector machines (SVM), respectively. The training dataset was composed of 46 positive samples (real sRNA-targets interaction) and 86 negative samples (no interaction between sRNA and targets).

Construction of mathematical model for high-level expression of foreign genes in pPIC9 vector and its verification.

In this report, we introduced a mathematical model for high-level expression of foreign genes in pPIC9 vector. At first, we collected 40 heterologous genes expressed in pPIC9 vector, and these 40 genes were classified into high-level expression group (expression level >100mg/L, 12 genes) and low-level expression group (expression level <100mg/L, 28 genes). Then, the Naive Bayes method was used to construct the model with RNA secondary structure profile of 3'-end of foreign genes as features.