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.     

Benthic macroinvertebrate biodiversity improved with irrigation ponds linked to a rice paddy field

Traditionally, many irrigation ponds supplied water to paddy fields, but most of these ponds have disappeared through improvements in irrigation systems. The aim of this study was to assess the ecological functions (especially biodiversity conservation) of irrigation ponds by using benthic macroinvertebrates that inhabit paddy fields. This study was conducted in Hwaseong‐si, Yesan‐gun, Hongseong‐gun, Uljin‐gun and Damyang‐gun, Korea. Benthic macroinvertebrates were collected using a quadrat sampler from August to September for three years (2010–2012) in paddy fields with and without an irrigation pond. In the comparisons between two paddy field types (paddy fields with and without an irrigation pond) for species richness and densities of benthic macroinvertebrates, the species richness and densities were higher in the paddy fields with a pond than in the paddy fields without a pond (P < 0.001). Biodiversity enhancement effect degree (BEED) of the irrigation pond showed positive values in all survey regions. There were no significant differences among the survey regions. BEED showed positive values in all taxonomic groups (excluding Crustacea) and were not significantly different among taxonomic groups. The BEED values for non‐insects, passive dispersers, were relatively higher than for insects, active dispersers. The results indicate that BEED is related to the dispersal abilities of each taxonomic group and an irrigation pond increases biodiversity in a paddy field in all regions. Therefore, the irrigation pond is one method that can be immediately applied in paddy fields in order to improve the biodiversity of agricultural ecosystems.     

Requirement of Fur for the full induction of Dps expression in Salmonella enterica serovar typhimurium

The Dps protein, which is overexpressed in harsh environments, is known to play a critical role in the protection of DNA against oxidative stresses. In this study, the roles of Fur in the expression of the dps gene in Salmonella and the protection mechanisms against oxidative stress in Salmonella cells preexposed to iron-stress were investigated. Two putative Fur boxes were predicted within the promoter region o f th e S. typhimurium dps gene . The profile of dps expression performed by the LacZ reporter assay revealed growth-phase dependency regardless of iron-status under the culture conditions. Thefur mutant, chi4659, evidenced a reduced level of beta-galactosidase as compared to the wild-type strain. The results observed after the measurement of the Dps protein in various Salmonella regulatory mutants were consistent with the results acquired in the reporter assay. This evidence suggested that Fur performs a function as a subsidiary regulator in the expression of dps. The survival ability of Salmonella strains after exposure to oxidative stress demonstrated that the Dps protein performs a pivotal function in the survival of stationary-phase S. typhimurium against oxidative stress. Salmonella cells grown in iron-restricted condition required Dps for full protection against oxidative stress. The CK24 (Deltadps) cells grown in iron-replete condition survived at a rate similar to that observed in the wild-type strain, thereby suggesting the induction of an unknown protection mechanism(s) other than Dps in this condition.     

A water-soluble extract from Cucurbita moschata shows anti-obesity effects by controlling lipid metabolism in a high fat diet-induced obesity mouse model

During the screening of a variety of plant sources for their anti-obesity activity, it was found that a water-soluble extract, named PG105, prepared from stem parts of Cucurbita moschata, contains potent anti-obesity activities in a high fat diet-induced obesity mouse model. In this animal model, increases in body weight and fat storage were suppressed by 8-week oral administration of PG105 at 500 mg/kg, while the overall amount of food intake was not affected. Furthermore, PG105 protected the development of fatty liver and increased the hepatic beta-oxidation activity. Results from blood analysis showed that the levels of triglyceride and cholesterol were significantly lowered by PG105 administration, and also that the level of leptin was reduced, while that of adiponectin was increased. To understand the underlying mechanism at the molecular level, the effects of PG105 were examined on the expression of the genes involved in lipid metabolism by Northern blot analysis. In the liver of PG105-treated mice, the mRNA level of lipogenic genes such as SREBP-1c and SCD-1 was decreased, while that of lipolytic genes such as PPARalpha, ACO-1, CPT-1, and UCP-2 was modestly increased. Our data suggest that PG105 may have great potential as a novel anti-obesity agent in that both inhibition of lipid synthesis and acceleration of fatty acid breakdown are induced by this reagent.