Absorption-based algorithm for satellite estimating the particulate organic carbon concentration in the global surface ocean

Particulate organic carbon (POC) in the surface ocean contributes to understanding the global ocean carbon cycle system. The surface POC concentration can be effectively detected using satellites. In open oceans, the blue-to-green band ratio (BG) algorithm is often used to obtain global surface ocean POC concentrations. However, POC concentrations are underestimated in waters with complex optical environments. To generate a more accurate global POC mapping in the surface ocean, we developed a new ocean color algorithm using a mixed global-scale in situ POC dataset with the concentration ranging from 11.10 to 4389.28 mg/m3. The new algorithm (a-POC) was established to retrieve the POC concentration using the strong relationship between the absorption coefficient at 490 nm (a(490)) and POC, in which a(490) was from the Ocean Color Climate Change Initiative (OC-CCI) v5.0 suite. Afterward, the a-POC algorithm was applied to OC-CCI v5.0 data for special regions and the global ocean. The performances of the a-POC algorithm and the BG algorithm were compared by combining the match-ups of satellite data and in situ dataset. The results showed that the statistical parameters of the a-POC algorithm were similar to those of the BG algorithm in the Atlantic oligotrophic gyre regions, with a median absolute percentage deviation (MAPD) value of 22.04%. In the eastern coastal waters of the United States and the Chesapeake Bay, the POC concentration retrieved by the a-POC algorithm was highly consistent with the match-ups, and MAPD values were 33.06% and 26.11%. The a-POC algorithm was also applied to the Ocean and Land Color Instrument (OLCI) data pre-processed with different atmospheric correction algorithms to evaluate the universality. The result showed that the a-POC algorithm was robust and less sensitive to atmospheric correction than the BG algorithm

Concept Design of the “Guanlan” Science Mission: China’s Novel Contribution to Space Oceanography

Among the various challenges that spaceborne radar observations of the ocean face, the following two issues are probably of a higher priority: inadequate dynamic resolution, and ineffective vertical penetration. It is therefore the vision of the National Laboratory for Marine Science and Technology of China that two highly anticipated breakthroughs in the coming decade are likely to be associated with radar interferometry and ocean lidar (OL) technology, which are expected to make a substantial contribution to a submesoscale-resolving and depth-resolving observation of the ocean. As an expanded follow-up of SWOT and an oceanic counterpart of CALIPSO, the planned “Guanlan” science mission comprises a dual-frequency (Ku and Ka) interferometric altimetry (IA), and a near-nadir pointing OL. Such an unprecedented combination of sensor systems has at least three prominent advantages. (i) The dual-frequency IA ensures a wider swath and a shorter repeat cycle which leads to a significantly improved temporal and spatial resolution up to days and kilometers. (ii) The first spaceborne active OL ensures a deeper penetration depth and an all-time detection which leads to a layered characterization of the optical properties of the subsurface ocean, while also serving as a near-nadir altimeter measuring vertical velocities associated with the divergence, and convergence of geostrophic eddy motions in the mixed layer. (iii) The simultaneous functioning of the IA/OL system allows for an enhanced correction of the contamination effects of the atmosphere and the air-sea interface, which in turn considerably reduces the error budgets of the two sensors. As a result, the integrated IA/OL payload is expected to resolve the ocean variability at submeso and sub-week scales with a centimeter-level accuracy, while also partially revealing marine life systems and ecosystems with a 10-m vertical interval in the euphotic layer, moving a significant step forward toward a “transparent ocean” down to the vicinity of the thermocline, both dynamically and bio-optically

A global view of porcine transcriptome in three tissues from a full-sib pair with extreme phenotypes in growth and fat deposition by paired-end RNA sequencing

<p>Abstract</p> <p>Background</p> <p>Elucidation of the pig transcriptome is essential for interpreting functional elements of the genome and understanding the genetic architecture of complex traits such as fat deposition, metabolism and growth.</p> <p>Results</p> <p>Here we used massive parallel high-throughput RNA sequencing to generate a high-resolution map of the porcine mRNA and miRNA transcriptome in liver, longissimus dorsi and abdominal fat from two full-sib F₂hybrid pigs with segregated phenotypes on growth, blood physiological and biochemical parameters, and fat deposition. We obtained 8,508,418-10,219,332 uniquely mapped reads that covered 78.0% of the current annotated transcripts and identified 48,045-122,931 novel transcript fragments, which constituted 17,085-29,499 novel transcriptional active regions in six tested samples. We found that about 18.8% of the annotated genes showed alternative splicing patterns, and alternative 3' splicing is the most common type of alternative splicing events in pigs. Cross-tissue comparison revealed that many transcriptional events are tissue-differential and related to important biological functions in their corresponding tissues. We also detected a total of 164 potential novel miRNAs, most of which were tissue-specifically identified. Integrated analysis of genome-wide association study and differential gene expression revealed interesting candidate genes for complex traits, such as <it>IGF2, CYP1A1, CKM </it>and <it>CES1 </it>for heart weight, hemoglobin, pork pH value and serum cholesterol, respectively.</p> <p>Conclusions</p> <p>This study provides a global view of the complexity of the pig transcriptome, and gives an extensive new knowledge about alternative splicing, gene boundaries and miRNAs in pigs. Integrated analysis of genome wide association study and differential gene expression allows us to find important candidate genes for porcine complex traits.</p

Design and baseline characteristics of the finerenone in reducing cardiovascular mortality and morbidity in diabetic kidney disease trial

Background: Among people with diabetes, those with kidney disease have exceptionally high rates of cardiovascular (CV) morbidity and mortality and progression of their underlying kidney disease. Finerenone is a novel, nonsteroidal, selective mineralocorticoid receptor antagonist that has shown to reduce albuminuria in type 2 diabetes (T2D) patients with chronic kidney disease (CKD) while revealing only a low risk of hyperkalemia. However, the effect of finerenone on CV and renal outcomes has not yet been investigated in long-term trials. Patients and Methods: The Finerenone in Reducing CV Mortality and Morbidity in Diabetic Kidney Disease (FIGARO-DKD) trial aims to assess the efficacy and safety of finerenone compared to placebo at reducing clinically important CV and renal outcomes in T2D patients with CKD. FIGARO-DKD is a randomized, double-blind, placebo-controlled, parallel-group, event-driven trial running in 47 countries with an expected duration of approximately 6 years. FIGARO-DKD randomized 7,437 patients with an estimated glomerular filtration rate >= 25 mL/min/1.73 m(2) and albuminuria (urinary albumin-to-creatinine ratio >= 30 to <= 5,000 mg/g). The study has at least 90% power to detect a 20% reduction in the risk of the primary outcome (overall two-sided significance level alpha = 0.05), the composite of time to first occurrence of CV death, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for heart failure. Conclusions: FIGARO-DKD will determine whether an optimally treated cohort of T2D patients with CKD at high risk of CV and renal events will experience cardiorenal benefits with the addition of finerenone to their treatment regimen. Trial Registration: EudraCT number: 2015-000950-39; ClinicalTrials.gov identifier: NCT02545049

Biomimetic Mineralization of CaCO3 on a Phospholipid Monolayer: From an Amorphous Calcium Carbonate Precursor to Calcite via Vaterite

A phospholipid monolayer, approximately half the bilayer structure of a biological membrane, can be regarded as an ideal model for investigating biomineralization on biological membranes. In this work on the biomimetic mineralization of CaCO3 under a phospholipid monolayer, we show the initial heterogeneous nucleation of amorphous calcium carbonate precursor (ACC) nanoparticles at the air-water interface, their subsequent transformation into the metastable vaterite phase instead of the most thermodynamically stable calcite phase, and the ultimate phase transformation to calcite. Furthermore, the spontaneity of the transformation from vaterite to calcite was found to be closely related to the surface tension; high surface pressure could inhibit the process, highlighting the determinant of surface energy. To understand better the mechanisms for ACC formation and the transformation from ACC to vaterite and to calcite, in situ Brewster angle microscopy (BAM), ex situ scanning electron microscopy, transmission electron microscopy. Raman spectroscopy, and X-ray diffraction analysis were employed. This work has clarified the crystallization process of calcium carbonate under phospholipid monolayers and therefore may further our understanding of the biomineralization processes induced by cellular membranes

A Turbidity-Compensation Method for Nitrate Measurement Based on Ultraviolet Difference Spectroscopy

To solve the problem that turbidity in water has a significant effect on the spectra of nitrate and reduces the accuracy of nitrate detection, a turbidity-compensation method for nitrate measurement based on ultraviolet difference spectra is proposed. The effect of turbidity on the absorption spectra of nitrate was studied by using the difference spectra of the mixed solution and a nitrate solution. The results showed that the same turbidity had different effects on the absorbance of different concentrations of nitrate. The change in absorbance due to turbidity decreased with an increase in the nitrate concentration at wavelengths from 200 nm to 230 nm, although this change was constant when the wavelength was greater than 230 nm. On the basis of this characteristic, we combined the residual sum of squares (RSS) and interval partial least squares (iPLS) to select wavelengths of 230&ndash;240 nm as the optimal modeling interval. Furthermore, the turbidity-compensation model was established by the linear fitting of the difference spectra of various levels of turbidity. The absorption spectra of the nitrate were extracted by subtracting the turbidity-compensation curve from the original spectra of the water samples, and the nitrate concentration was calculated by using a partial least squares (PLS)-based nitrate-prediction model. The experimental results showed that the average relative error of the nitrate predictions was reduced by 50.33% to 1.33% by the proposed turbidity-compensation method. This indicated that this method can better correct the deviation in nitrate&rsquo;s absorbance caused by turbidity and improve the accuracy of nitrate predictions

Lidar Concept of “Guanlan” Mission for Space Oceanography

Among the various challenges in spaceborne radar observation of the ocean, the following two issues are probably of a higher priority: inadequate dynamic resolution, and ineffective vertical penetration. Two highly anticipated breakthroughs in the coming decade are likely to be associated with radar interferometry and ocean lidar technology, which are expected to make a substantial contribution to a sub-mesoscale-resolving and depth-resolving observation of the ocean. The planned “Guanlan” science mission comprises a dual-frequency (Ku and Ka) interferometric altimetry (IA) and a near-nadir pointing ocean lidar (OL). The spaceborne active OL will ensure a deeper penetration depth and an all-time detection which leads to a layered characterization of the optical properties of the subsurface ocean. The simultaneous functioning of the OL and a dual-frequency (Ku and Ka) interferometric altimetry system will allow an enhanced understanding of contributions of the atmosphere and the air-sea interface which in turn considerably reduce the error budgets of the two sensors. The OL payload is expected to partially reveal the marine food chain and ecosystem with 10-m vertical interval in the euphotic layer, moving a significant step down to the oceanic mixed layer both dynamically and bio-optically