Quantification of gas hydrate saturation and morphology based on a generalized effective medium model

Highlights • A modified cementation theory is developed by introducing generalized pressure-dependent normalized contact-cemented radii. • A generalized effective medium model is proposed to merge the effective medium theory and cementation theory. • Modeling and inversion schemes are proposed to quantify hydrate saturation and morphology from laboratory and well-log data. • Hydrates mainly grow as matrix-supporting form (~54%) in sands and as pore-filling form (~59%) in clay-rich marine sediments. Abstract Numerous models have been developed for prediction of gas hydrate saturation based on the microstructural relationship between gas hydrates and sediment grains. However, quantification of hydrate saturation and morphology from elastic properties has been hindered by failing to account for complex hydrate distributions. Here, we develop a generalized effective medium model by applying the modified Hashin-Shtrikman bounds to a newly developed cementation theory. This model is validated by experimental data for synthetic methane and tetrahydrofuran hydrates. Good comparison of model predictions with experimental measurements not only reveals its ability to merge the results of contact cementation theory and effective medium theory, but also indicates its feasibility for characterizing complex morphologies. Moreover, the results of inverting acoustic measurements quantitatively confirm that for synthetic samples in “excess-gas” condition gas hydrates mainly occur as a hybrid-cementing morphology with a low percentage of pore-filling morphology, whereas for pressure-core hydrate-bearing sediments in natural environments they exist as matrix-supporting and pore-filling morphologies with a very low percentage of hybrid-cementing morphology. The hydrate saturations estimated from sonic and density logs in several regions including northern Cascadia margin (Integrated Ocean Drilling Program Expedition 311, Hole U1326D and Hole U1327E), Alaska North Slope (Mount Elbert test well) and Mackenzie Delta (Mallik 5L-38), are comparable to the referenced hydrate saturations derived from core data and resistivity, and/or nuclear magnetic resonance log data, confirming validity and applicability of our model. Furthermore, our results indicate that ~8% hybrid-cementing, ~33% matrix-supporting and ~59% pore-filling hydrates may coexist in the fine-grained and clay-rich marine sediments on the northern Cascadia margin, whereas ~10% hybrid-cementing, ~54% matrix-supporting and ~36% pore-filling hydrates may coexist in the coarse-grained and sand-dominated terrestrial sediments of the Alaska North Slope and Mackenzie Delta

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

A Hybrid Data‐Driven and Data Assimilation Method for Spatiotemporal Forecasting: PM2.5 Forecasting in China

Abstract Spatiotemporal forecasting involves generating temporal forecasts for system state variables across spatial regions. Data‐driven methods such as Convolutional Long Short‐Term Memory (ConvLSTM) are effective in capturing both spatial and temporal correlations, but they suffer from error accumulation and accuracy loss as forecasting time increases due to the nonlinearity and uncertainty in physical processes. To address this issue, we propose to combine data‐driven and data assimilation (DA) methods for spatiotemporal forecasting. The accuracy of the data‐driven ConvLSTM model can be improved by periodically assimilating real‐time observations using the ensemble Kalman filter (EnKF) approach. This proposed hybrid ConvLSTM‐EnKF method is demonstrated through PM2.5 forecasting in China, which is a challenging task due to the complexity of topographical and meteorological conditions in the region, the need for high‐resolution forecasting over a large study area, and the scarcity of observations. The results show that the ConvLSTM‐EnKF method outperforms conventional methods and can provide satisfactory operational PM2.5 forecasts for up to 1 month with spatially averaged RMSE below 20 μg/m3 and correlation coefficient (R) above 0.8. In addition, the ConvLSTM‐EnKF method shows a substantial reduction in CPU time when compared to the commonly used NAQPMS‐EnKF method, up to three orders of magnitude. Overall, the use of data‐driven models provides efficient forecasts and speeds up DA. This hybrid ConvLSTM‐EnKF is a novel operational forecasting technique for spatiotemporal forecasting and is used in real spatiotemporal forecasting for the first time

Testosterone Deficiency Induces Changes of the Transcriptomes of Visceral Adipose Tissue in Miniature Pigs Fed a High-Fat and High-Cholesterol Diet

Testosterone deficiency causes fat deposition, particularly in visceral fat, and its replacement might reverse fat accumulation, however, the underlying mechanisms of such processes under diet-induced adiposity are largely unknown. To gain insights into the genome-wide role of androgen on visceral adipose tissue (VAT), RNA-Seq was used to investigate testosterone deficiency induced changes of VAT in miniature pigs fed a high-fat and high-cholesterol (HFC) diet among intact male pigs (IM), castrated male pigs (CM), and castrated male pigs with testosterone replacement (CMT) treatments. The results showed that testosterone deficiency significantly increased VAT deposition and serum leptin concentrations. Moreover, a total of 1732 differentially expressed genes (DEGs) were identified between any two groups. Compared with gene expression profiles in IM and CMT pigs, upregulated genes in CM pigs, i.e., LOC100520753 (CD68), LCN2, EMR1, S100A9, NCF1 (p47phox), and LEP, were mainly involved in inflammatory response, oxidation-reduction process, and lipid metabolic process, while downregulated genes in CM pigs, i.e., ABHD5, SPP1, and GAS6, were focused on cell differentiation and cell adhesion. Taken together, our study demonstrates that testosterone deficiency alters the expression of numerous genes involved in key biological processes of VAT accumulation under HFC diet and provides a novel genome-wide view on the role of androgen on VAT deposition under HFC diet, thus improving our understanding of the molecular mechanisms involved in VAT changes induced by testosterone deficiency

MicroRNA Expression Profiling of the Porcine Developing Hypothalamus and Pituitary Tissue

MicroRNAs (miRNAs), a class of small non-coding RNA molecules, play important roles in gene expressions at transcriptional and post-transcriptional stages in mammalian brain. So far, a growing number of porcine miRNAs and their function have been identified, but little is known regarding the porcine developing hypothalamus and pituitary. In the present study, Solexa sequencing analysis showed 14,129,397 yielded reads, 6,680,678 of which were related to 674 unique miRNAs. After a microarray assay, we detected 175 unique miRNAs in the hypothalamus, including 136 previously known miRNAs and 39 novel candidates, while a total of 140 miRNAs, including 104 known and 36 new candidate miRNAs, were discovered in pituitary. More importantly, 37 and 30 differentially expressed miRNAs from several developmental stages of hypothalamus and pituitary were revealed, respectively. The 37 differentially expressed miRNAs in hypothalamus represented 6 different expression patterns, while the 30 differentially expressed miRNAs in pituitary represented 7 different expression patterns. To clarify potential target genes and specific functions of these differentially expressed miRNAs in hypothalamus and pituitary, TargetScan and Gorilla prediction tools were then applied. The current functional analysis showed that the differentially expressed miRNAs in hypothalamus and pituitary shared many biological processes, with the main differences being found in tissue-specific processes including: CDP-diacylglycerol biosynthetic/metabolic process; phosphatidic acid biosynthetic/metabolic process; energy reserve metabolic process for hypothalamus; adult behavior; sterol transport/homeostasis; and cholesterol/reverse cholesterol transport for pituitary. Overall, this study identified miRNA profiles and differentially expressed miRNAs among various developmental stages in hypothalamus and pituitary and indicated miRNA profiles change with age and brain location, enhancing our knowledge about spatial and temporal expressions of miRNAs in the porcine developing brain