Codon usage bias analysis of genes linked with esophagus cancer

Esophageal cancer involves multiple genetic alternations. A systematic codon usage bias analysis was completed to investigate the bias among the esophageal cancer responsive genes. GC-rich genes were low (average effective number of codon value was 49.28). CAG and GTA are over-represented and under-represented codons, respectively. Correspondence analysis, neutrality plot, and parity rule 2 plot analysis confirmed the dominance over mutation pressure in modulating the codon usage pattern of genes linked with esophageal cancer.     

A vesicular stomatitis virus-based prime-boost vaccination strategy induces potent and protective neutralizing antibodies against SARS-CoV-2

The development of safe and effective vaccines to prevent SARS-CoV-2 infections remains an urgent priority worldwide. We have used a recombinant vesicular stomatitis virus (rVSV)-based prime-boost immunization strategy to develop an effective COVID-19 vaccine candidate. We have constructed VSV genomes carrying exogenous genes resulting in the production of avirulent rVSV carrying the full-length spike protein (S_F), the S1 subunit, or the receptor-binding domain (RBD) plus envelope (E) protein of SARS-CoV-2. Adding the honeybee melittin signal peptide (msp) to the N-terminus enhanced the protein expression, and adding the VSV G protein transmembrane domain and the cytoplasmic tail (Gtc) enhanced protein incorporation into pseudotype VSV. All rVSVs expressed three different forms of SARS-CoV-2 spike proteins, but chimeras with VSV-Gtc demonstrated the highest rVSV-associated expression. In immunized mice, rVSV with chimeric S protein-Gtc derivatives induced the highest level of potent neutralizing antibodies and T cell responses, and rVSV harboring the full-length msp-S_F-Gtc proved to be the superior immunogen. More importantly, rVSV-msp-S_F-Gtc vaccinated animals were completely protected from a subsequent SARS-CoV-2 challenge. Overall, we have developed an efficient strategy to induce a protective response in SARS-CoV-2 challenged immunized mice. Vaccination with our rVSV-based vector may be an effective solution in the global fight against COVID-19.     

A new method of studying predatory nematodes using a micropore system

We developed an innovative micropore system that enables us to directly observe the constrained behaviour of predatory nematodes. The results show that the new system provides a suitable environment for modelling the potential effects of these animals as biocontrol agents in their natural habitat.     

Progressive hypoxia-on-a-chip: An in vitro oxygen gradient model for capturing the effects of hypoxia on primary hepatocytes in health and disease

Oxygen is vital to the function of all tissues including the liver and lack of oxygen, that is, hypoxia can result in both acute and chronic injuries to the liver in vivo and ex vivo. Furthermore, a permanent oxygen gradient is naturally present along the liver sinusoid, which plays a role in the metabolic zonation and the pathophysiology of liver diseases. Accordingly, here, we introduce an in vitro microfluidic platform capable of actively creating a series of oxygen concentrations on a single continuous microtissue, ranging from normoxia to severe hypoxia. This range approximately captures both the physiologically relevant oxygen gradient generated from the portal vein to the central vein in the liver, and the severe hypoxia occurring in ischemia and liver diseases. Primary rat hepatocytes cultured in this microfluidic platform were exposed to an oxygen gradient of 0.3–6.9%. The establishment of an ascending hypoxia gradient in hepatocytes was confirmed in response to the decreasing oxygen supply. The hepatocyte viability in this platform decreased to approximately 80% along the hypoxia gradient. Simultaneously, a progressive increase in accumulation of reactive oxygen species and expression of hypoxia-inducible factor 1α was observed with increasing hypoxia. These results demonstrate the induction of distinct metabolic and genetic responses in hepatocytes upon exposure to an oxygen (/hypoxia) gradient. This progressive hypoxia-on-a-chip platform can be used to study the role of oxygen and hypoxia-associated molecules in modeling healthy and injured liver tissues. Its use can be further expanded to the study of other hypoxic tissues such as tumors as well as the investigation of drug toxicity and efficacy under oxygen-limited conditions.     

Canopy-cover thematic-map generation for Military Map products using remote sensing data in inaccessible areas

Canopy cover is one of the most important elements in concealing military structures and enemy reconnaissance. In this study, we propose an algorithm for automatic generation of density measure of percent canopy cover, which is an attribute of the digital Military Map product, using high-resolution satellite images of inaccessible areas. The thematic mapping process of canopy cover can be divided into image classification, segmentation, and texture analysis. QuickBird and SPOT-5 high-resolution images are classified using Landsat images and military maps. Then, forested areas are extracted from the classified images, and closing and opening operations are executed through morphology filtering. The extracted region is divided into unit-zone objects using a segmentation technique, and the percentage of canopy cover of each object is categorized as one of four levels (0–25, 26–50, 51–75, 76–100%). Two methods were used to establish the percentage of canopy cover for each segment: the discriminant method, using statistical analysis, and the classified canopy ratio method, which calculates the percentage of forest in the segment. The discriminant method showed 48% (QuickBird) and 61% (SPOT-5) accuracy and classified canopy ratio method showed 71% (QuickBird) and 87% (SPOT-5) accuracy.     

Outlier Detection using Projection Quantile Regression for Mass Spectrometry Data with Low Replication

ABSTRACT: BACKGROUND: Mass spectrometry (MS) data are often generated from various biological or chemical experiments and there may exist outlying observations, which are extreme due to technical reasons. The determination of outlying observations is important in the analysis of replicated MS data because elaborate pre-processing is essential for successful analysis with reliable results and manual outlier detection as one of pre-processing steps is time-consuming. The heterogeneity of variability and low replication are often obstacles to successful analysis, including outlier detection. Existing approaches, which assume constant variability, can generate many false positives (outliers) and/or false negatives non-outliers). Thus, a more powerful and accurate approach is needed to account for the heterogeneity of variability and low replication. FINDINGS: We proposed an outlier detection algorithm using projection and quantile regression in MS data from multiple experiments. The performance of the algorithm and program was demonstrated by using both simulated and real-life data. The projection approach with linear, nonlinear, or nonparametric quantile regression was appropriate in heterogeneous high-throughput data with low replication. CONCLUSION: Various quantile regression approaches combined with projection were proposed for detecting outliers. The choice among linear, nonlinear, and nonparametric regressions is dependent on the degree of heterogeneity of the data. The proposed approach was illustrated with MS data with two or more replicates.