Lack of incremental value of three-dimensional measurement in assessing invasiveness for lung cancer.

Objectives: The aim of this study was to evaluate the performance of consolidation-to-tumour ratio (CTR) and the radiomic models in two- and three-dimensional modalities for assessing radiological invasiveness in early-stage lung adenocarcinoma.

Methods: A retrospective analysis was conducted on patients with early-stage lung adenocarcinoma from Guangdong Provincial People's Hospital and Shenzhen People's Hospital. Manual delineation of pulmonary nodules along the boundary was performed on cross-sectional images to extract radiomic features.

Toward an Expert Level of Lung Cancer Detection and Classification Using a Deep Convolutional Neural Network.

Background: Computed tomography (CT) is essential for pulmonary nodule detection in diagnosing lung cancer. As deep learning algorithms have recently been regarded as a promising technique in medical fields, we attempt to integrate a well-trained deep learning algorithm to detect and classify pulmonary nodules derived from clinical CT images.

Materials And Methods: Open-source data sets and multicenter data sets have been used in this study.

[Strategy of selecting 16S rRNA hypervariable regions for metagenome-phylogenetic marker genes based analysis].

The advent of next generation sequencing technology enables parallel analysis of the whole microbial community from multiple samples. Particularly, sequencing 16S rRNA hypervariable tags has become the most efficient and cost-effective method for assessing microbial diversity. Due to its short read length of the 2nd-generation sequencing methods that cannot cover the full 16S rRNA genomic region, specific hypervariable regions or V-regions must be selected to act as the proxy.

Complicated evolutionary patterns of microRNAs in vertebrates.

MicroRNAs (miRNAs) are a class of approximately 22 nt long endogenous non-coding RNAs that play important regulatory roles in diverse organisms. Up to now, little is known about the evolutionary properties of these crucial regulators. Most miRNAs were thought to be phylogenetically conserved, but recently, a number of poorly-conserved miRNAs have been reported and miRNA innovation is shown to be an ongoing process.

Discovering multiple transcripts of human hepatocytes using massively parallel signature sequencing (MPSS).

Background: The liver is the largest human internal organ--it is composed of multiple cell types and plays a vital role in fulfilling the body's metabolic needs and maintaining homeostasis. Of these cell types the hepatocytes, which account for three-quarters of the liver's volume, perform its main functions. To discover the molecular basis of hepatocyte function, we employed Massively Parallel Signature Sequencing (MPSS) to determine the transcriptomic profile of adult human hepatocytes obtained by laser capture microdissection (LCM).

[Determination of geographical origins of Chinese medical herbs by NIR and pattern recognition].

Geographical origin of medical herbs is an important factor of the quality of many traditional Chinese herbal medicines. The objective of the present study is to investigate whether NIR spectroscopy coupled with pattern recognition techniques could effectively discriminate geographical origins of medical herbs. Nearest neighbor method (NNM) and a SVM-based multiclass classifier were employed to discriminate 269 Angelicae Dahuricae Radix (ADR) samples from 4 provinces and 380 Salviae Miltiorrhizae Radix (SMR) samples from 6 provinces in China.

Characterizing the microenvironment surrounding phosphorylated protein sites.

Protein phosphorylation plays an important role in various cellular processes. Due to its high complexity, the mechanism needs to be further studied. In the last few years, many methods have been contributed to this field, but almost all of them investigated the mechanism based on protein sequences around protein sites.

[Use of FTIR and pattern recognition to determine geographical origins of Chinese medical herbs].

Geographical origin of medical herbs is an important factor of the quality of many traditional Chinese herbal medicines. The objective of this study is to investigate whether FTIR spectroscopy coupled with pattern recognition techniques could effectively discriminate geographical origins of medical herbs. Nearest neighbor method (NNM) and a SVM-based multiclass classifier were employed to discriminate 269 angelicae dahuricae radix (ADR) samples from 4 provinces in China and 380 salviae miltiorrhizae radix (SMR) samples from 6 provinces.