Identifying local associations in biological time series: algorithms, statistical significance, and applications.

Local associations refer to spatial-temporal correlations that emerge from the biological realm, such as time-dependent gene co-expression or seasonal interactions between microbes. One can reveal the intricate dynamics and inherent interactions of biological systems by examining the biological time series data for these associations. To accomplish this goal, local similarity analysis algorithms and statistical methods that facilitate the local alignment of time series and assess the significance of the resulting alignments have been developed. Although these algorithms were initially devised for gene expression analysis from microarrays, they have been adapted and accelerated for multi-omics next generation sequencing datasets, achieving high scientific impact. In this review, we present an overview of the historical developments and recent advances for local similarity analysis algorithms, their statistical properties, and real applications in analyzing biological time series data. The benchmark data and analysis scripts used in this review are freely available at http://github.com/labxscut/lsareview.

Ksak: A high-throughput tool for alignment-free phylogenetics.

Phylogenetic tools are fundamental to the studies of evolutionary relationships. In this paper, we present Ksak, a novel high-throughput tool for alignment-free phylogenetic analysis. Ksak computes the pairwise distance matrix between molecular sequences, using seven widely accepted k-mer based distance measures. Based on the distance matrix, Ksak constructs the phylogenetic tree with standard algorithms. When benchmarked with a golden standard 16S rRNA dataset, Ksak was found to be the most accurate tool among all five tools compared and was 19% more accurate than ClustalW2, a high-accuracy multiple sequence aligner. Above all, Ksak was tens to hundreds of times faster than ClustalW2, which helps eliminate the computation limit currently encountered in large-scale multiple sequence alignment. Ksak is freely available at https://github.com/labxscut/ksak.

The downregulation of ANGPTL4 inhibits the migration and proliferation of tongue squamous cell carcinoma.

OBJECTIVE: Tongue squamous cell carcinoma (TSCC) is the most common malignant cancer in the oral cavity, with a high rate of metastasis to the neck lymphoid node. Angiopoietin-like protein 4 (ANGPTL4) and microvessel density (MVD) may be novel indicators for tumor metastasis. The aim of the present study was to investigate the expression and function of ANGPTL4 in TSCC and the relationship between ANGPTL4 and MVD. METHODS: The expression levels of ANGPTL4 and MVD (CD34) were analyzed in 65 TSCC specimens and the adjacent non-cancerous tissues using immunohistochemistry (IHC). siRNA was delivered into TSCCA cells to downregulate ANGPTL4 expression. Subsequently, validation with real-time RT-PCR and western blot analyses was performed to analyze ANGPTL4 expression levels. In addition, a proliferation assay, migration and invasion assays were carried out. RESULTS: ANGPTL4 expression was associated with tumor stage, lymph node metastasis and MVD expression. Cox regression analysis showed that high levels of ANGPTL4 expression were closely associated with poor survival time. In vitro analyses using qRT-PCR and western blot confirmed that ANGPTL4 was successfully inhibited in TSCCA cells. Suppressing ANGPTL4 resulted in the inhibition of cell proliferation and migration, but neither invasion nor cisplatin resistance was significantly affected. CONCLUSION: High expression levels of ANGPTL4 are associated with the T stage, lymphatic metastasis, angiogenesis and poor overall survival in TSCC patients. The downregulation of ANGPTL4 inhibits the migration and proliferation of cells in TSCC. Taken together, ANGPTL4 may serve as a novel biomarker and therapeutic target for TSCC.

A two-dimensional model on the coupling thickness-shear vibrations of a quartz crystal resonator loaded by an array spherical-cap viscoelastic material units.

We establish a two-dimensional model on the coupling thickness-shear mode (TSM) vibrations of a quartz crystal resonator (QCR) carrying an array of spherical-cap (SC) viscoelastic material units. The electrical admittance of the compound QCR system is described directly in terms of the physical properties of the surface material units. The admittance spectra about the tendon stem cells (TSCs) acquired from our calculation are compared with the existing experiment data and found to be consistent with each other, indicating our model has good veracity and reliability in analyzing the mechanical properties of covered loadings. Furthermore, we calculate admittance spectra of surface Epoxy Resin (SU-8) units with different geometrical configurations and bulk effect. It is found that both geometrical configuration and bulk effect produce influence on the resonant frequency and admittance of the compound QCR system.