bluuebunny/crossref_metadata_2025 huggingface dataset:
Vaca Muerta's Productivity and Economic Performance. 7 Years in Review
Authors: Gilardone Carlos R. , Canel Carlos A. , Albuquerque Luisa , Ruiz Benitez Manuel I. , Cabello Ariel
Published: September 2021

Vaca Muerta is an unconventional reservoir located in Argentina. Since 2014, 397 horizontal wells have been drilled in this formation. The scope of this paper is to summarize the evolution of the productivity and the economics of these wells from 2014 until 2020.

The methodology consisted in analyzing the results of the wells grouped by drilling campaign extracting the main parameters such as peak oil rate, cumulative oil at 365 days, number of fracture stages and length of the drain. After the extraction of these parameters we calculated each well's EUR using a modified hyperbolic function. A statistical analysis of the results was performed in order to calculate a "Type Well" for each drilling campaign. An economic evaluation for each campaign was then generated in order determine the "Type Well" economics.

Once this was achieved we calculated the production profile of an "Economic Type Well" for each campaign defining this as the well which would generate an NPV=0$ at a discount rate of 10%. This was used to determine how many wells were economical for each year.

The results of this study show the big impact on the productivity generated by the increase in well length and the number of frac stages revealing the progression of the "Learning curve" for the Vaca Muerta basin including the reduction in Capital Expenditures per well.

At present, Vaca Muerta represents an opportunity as a profitable play due to the high productivity of the reservoir and low risk. Nevertheless, there is still room for improvement in the wells' cost according to the results of this study.

This paper presents the evolution of the economics and the risk performance of Vaca Muerta.
Modeling Boundary-Dominated Flow in Hydraulically-Fractured Wells
Authors: Sheikh Hafiz Mustafa Ud Din , Lee W. J. , Jha H. S.
Published: September 2021

This paper presents a simple method to model boundary-dominated flow in hydraulically fractured wells, including horizontal wells with multiple fractures. While these wells are almost always producedat more nearly constant BHP rather than constant rate, use of material-balance time transforms variable-rate production profiles to constant-rate profiles, allowing us to use the pseudo-steady-state (PSS) flow equation for modeling. However, the PSS equation requires use of shape factors in applications, and shape factors available in the literature are available only for square-shaped bounded reservoirs with hydraulic fractures. In this work, we derived shape factors for wells centered in rectangular-shaped drainage areas with different length-to-width aspect ratios.

The superposition principle can be used to transform transient radial flow and transient linear flow solutions into bounded reservoir solutions. At large times (when boundary-dominated flow is established), results from these solutions are similar to those obtained from the PSS equation. Therefore, for a pre-defined reservoir geometry, pressure drop values from superimposed transient flow equationscan be substituted back into the PSS equation to calculate shape factors for that reservoir geometry.We used shape factors previously presented by other authors for square drainage areas to validate themethod before applying it to calculate shape factors for more general drainage area configurations.

We present shape factors for different fracture half-length to fracture-spacing ratios ranging from 0.2 to 10. Calculated shape factors, when plotted against the fracture half-length to fracture-spacing ratio, produced a smooth curve which can be used to interpolate shape factor values for other fracture configurations. We present applications of this methodology to example low-permeability wells.

The use of the PSS equation for wells with vertical fracturescan be extended to multi-fractured horizontal wells (MFHWs) by incorporating the number of fractures in the equation; hence, shape factorsderived for wells with vertical fractures can also be used for MFHWs. Although our results are rigorously correct only for fluids with constant compressibility, use of pseudo-pressure and pseudo-time transformations extend application to compressible fluids, notably gases. Using the PSS equation in production data analysis allows us to calculate contributing reservoir volume and drainage area in a simple manner not requiring use of specialized software.
Fracture Permeability Estimation Under Complex Physics: A Data-Driven Model Using Machine Learning
Authors: He Xupeng , Zhu Weiwei , Santoso Ryan , Alsinan Marwa , Kwak Hyung , Hoteit Hussein
Published: September 2021

The permeability of fractures, including natural and hydraulic, are essential parameters for the modeling of fluid flow in conventional and unconventional fractured reservoirs. However, traditional analytical cubic law (CL-based) models used to estimate fracture permeability show unsatisfactory performance when dealing with different dynamic complexities of fractures. This work presents a data-driven, physics-included model based on machine learning as an alternative to traditional methods. The workflow for the development of the data-driven model includes four steps. Step 1: Identify uncertain parameters and perform Latin Hypercube Sampling (LHS). We first identify the uncertain parameters which affect the fracture permeability. We then generate training samples using LHS. Step 2: Perform training simulations and collect inputs and outputs. In this step, high-resolution simulations with parallel computing for the Navier-Stokes equations (NSEs) are run for each of the training samples. We then collect the inputs and outputs from the simulations. Step 3: Construct an optimized data-driven surrogate model. A data-driven model based on machine learning is then built to model the nonlinear mapping between the inputs and outputs collected from Step 2. Herein, Artificial Neural Network (ANN) coupling with Bayesian optimization algorithm is implemented to obtain the optimized surrogate model. Step 4: Validate the proposed data-driven model. In this step, we conduct blind validation on the proposed model with high-fidelity simulations. We further test the developed surrogate model with newly generated fracture cases with a broad range of roughness and tortuosity under different Reynolds numbers. We then compare its performance to the reference NSEs solutions. Results show that the developed data-driven model delivers good accuracy exceeding 90% for all training, validation, and test samples. This work introduces an integrated workflow for developing a data-driven, physics-included model using machine learning to estimate fracture permeability under complex physics (e.g., inertial effect). To our knowledge, this technique is introduced for the first time for the upscaling of rock fractures. The proposed model offers an efficient and accurate alternative to the traditional upscaling methods that can be readily implemented in reservoir characterization and modeling workflows.
A Field Pilot of Waterflooding Conformance Control in Tight Oil Reservoir with Biotechnology
Authors: Liu Songyuan , Jin Xiaochun , Liu Deji , Xu Hao , Zhang Lidong , Zhou Xiaosong , Huang Peng , Thomspson James , Lu Bo
Published: September 2021

Traditional Microbial Enhanced Oil Recovery (MEOR) technology assumes the oil recovery is increased by the biosurfactant generating by the subsurface bacteria. However, we identified that increased recovery factor is mainly contributed by stimulating the indigenous bacteria to plug the preferred waterflooding channels, which was proved at laboratory and some high-permeable oilfield, but never implemented in the waterflooding of tight oilfield. This paper presents a comprehensive study on Bio-diversion technique by stimulating indigenous bacteria covering lab research and filed operation lasting 18 months. The lab research comprised: (1) feasibility research using modified recipe and field sample on the stimulation of indigenous microorganisms; and (2) Evaluation of effectiveness of the stimulation based on lab results. A field pilot, consisting of 10 injectors, 10 producers, injecting and producing from multi-zones, reservoir temperature is about 160 F, permeabilities range from 30 md to over 100 md, daily water injection rate is about 2,000 BWPD, pre-treatment water cut is over 90%. It is observed that the water cut has decreased from 98% to 80% gradually (3-6 months after injection). Besides, the water injection index test indicates that the injection profile becomes more evenly after 9 months of microbial nutrient injection because the stimulated bacteria reduce the permeability of more permeable zones and reduce the permeability heterogeneity in the vertical direction. Sharing the field results with the industry may inspire the operators to consider one alternative environmentally friendly and cost-effective approach to increase the recovery factor of tight oil reservoirs. From the technical viewpoint, the field pilot proves that the major mechanisms of MEOR is sweeping the unswept oil by injecting the microbial nutrient to the reservoir to stimulate the indigenous bacteria to block the preferred waterflooding channels.
Automated Subsurface Knowledge ASK Thamama Retrieval Engine Driven by Conversational Text Analytics and NLP - Lessons Learned in Managing Large Volume of Documents in Abu Dhabi Assets
Authors: Braik Fahed Mubarak , Al Shehhi Abdulla Sulaiman , Saputelli Luigi , Mata Carlos , Badmaev Dorzhi , Khan Salman , Rahman Fariz
Published: September 2021

The purpose of this paper is to communicate the experiences in the development of an innovative concept named "ASK Thamama" as an automated data and information retrieval engine driven by artificial intelligence techniques including text analytics and natural language processing. ASK is an AI enabled conversational search engine used to retrieve information from various internal data repositories using natural language queries. The text processing and conversational engine concept is built upon available open-source software requiring minimum coding of new libraries.

A data set with 1000 documents was used to validate key functionalities with an accuracy of 90% of the search queries and able to provide specific answers for 80% of queries framed as questions.

The results of this work show encouraging results and demonstrate value that AI-enabled methodologies can provide natural language search by enabling automated workflows for data information retrieval. The developed AI methodology has tremendous potential of integration in an end-to-end workflow of knowledge management by utilizing available document repositories to valuable insights, with little to no human intervention.
How to Space SAGD Well Pairs for Optimal Performance
Authors: Zargar Zeinab , Farouq Ali S. M.
Published: September 2021

Steam-Assisted Gravity Drainage (SAGD) is a remarkably successful process for the tar sands (oil sands). Two closely spaced parallel horizontal wells, injector above the producer, form a SAGD well pair. Steam is injected to provide heat to the reservoir oil and mobilize it. The low viscosity oil drains down to the producer under the gravity effect. Parallel well pairs 1000 m long are utilized in the process, spaced 100 m apart horizontally almost in all projects.

In this work, an analytical model for the SAGD process is introduced by coupling heat and fluid flow and constitutive equations. A moving boundary, counter-current flow approach is used for the steam chamber rise and subsequent sideways expansion. The model is unique because it assumes the steam injection rate is constant and it permits modeling of the late phase of SAGD when adjacent well pair interference occurs. This leads to a reduction in heat loss to the overburden and a decline in oil production rate. This study examines the question of optimal well pair spacing in relation to the formation thickness and in-place oil. The effect of other variables on SAGD performance is investigated.

A case study was performed using Christina Lake oil sand properties to show how the project performance varies under different senerios involving well pair spacing, reservoir thickness, steam injection rate, and steam quality. Results show that, in evaluating a SAGD pad performance, as the spacing is increased, the cumulative oil production decreases, with a simultanous increase in the cumulative steam-oil ratio at the same steam injection rate. However, a smaller portion of injected heat is lost to the overburden. It is concluded that a smaller well spacing requires more wells to deplete the whole pad area. On the other hand, a larger pattern well spacing affects oil recovery and heat consumption. Different conclusions are derived for the same pattern well spacing value using a single well pair model and pattern well pair configuration. Results also show that SAGD well pair spacing can be increased with an increase in formation thickness.

The computational procedure is simple and makes it possible to examine a series of options for well spacing for a given set of conditions. This study presents for the first time an analytical relation between SAGD pattern well pair spacing and oil recovery.
Proppant Transport in Hydraulic Fractures by Creating a Capillary Suspension
Authors: Bello Ayomikun
Published: September 2021

Slick water fracturing fluids with high viscosity and minimal friction pressure losses are commonly employed in hydraulic fracturing nowadays. At the same time, high injection rates can be used to perform hydraulic fracturing to get the calculated fracture sizes.

The conventional algorithm for conducting a standard proppant hydraulic fracturing includes performing a pressure test using a linear gel without a trial proppant pack to determine the quality of communication with the formation and the initial parameters of the fracture; and performing a mini-hydraulic fracturing on a cross-linked gel with a trial proppant pack (1000 - 2000 kg) to assess the parameters of the fracture development used to correct the design of the main hydraulic fracturing operation.

However, in complex geological conditions associated with the presence of small clay barriers between the target formation and above or below the water-saturated layers, as well as in low-productive formations, this conventional method of conducting hydraulic fracturing operations using high-viscosity fluids is not always suitable. Hydraulic fracturing in thin-layer formations is associated with a significant risk of the tightness established by the fracture being broken, as well as fluids contained in the underlying or overlying layers being involved in the drainage process.

Hydraulic fracturing in low-productive formations creates fractures that are similar in shape to radial fractures, reducing the efficiency and profitability of the impact due to inefficient use of materials and reagents. The main task in this situation is to limit the height of the fracture development and increase their length. It is necessary to use low-viscosity fracturing fluids with a high ability to transfer proppants to reduce the specific pressure in the fracture and control the height of the rupture. The goal of this research is to develop such fluid.
Integrating XRD and Well Logging Data to Establish Electro-Facies and Permeability Models for an Unconventional Heterogeneous Tight Gas Reservoir, Obaiyed Giant Gas Field
Authors: Mabrouk Ibrahim
Published: September 2021

Formation evaluation in heterogeneous reservoirs can be very challenging especially in fields that extend over several kilometers in area where the permeability varies from 0.1 mD up to 1000 D within the same porosity. The porosity, hydrocarbon saturation and net sand thickness in most of Obaiyed field wells are consistent; hence, the productivity of these wells is enormously dependent on the reservoir permeability. Since the permeability is highly heterogeneous, initial production rate of the wells varies between few MMSCFD to almost one hundred MMSCFD.

The huge permeability variation led to a tremendous uncertainty in the dynamic modeling, which resulted in an inaccurate production forecast affecting the field economics estimation. Understanding permeability distribution and heterogeneity in Obaiyed field is the key factor for establishing a realistic permeability model, which will lead to a successful field development strategy. Extensive work was performed to understand key factors that govern the permeability in Obaiyed using the data of 1-kilometer length of cores acquired in more than 50 wells covering different reservoir properties in the field.

Core data were used to separate the reservoir into different Hydraulic Flow Units (HFU) according to Amaefule's work performed on the Kozeny-Carmen model. Afterwards, a correlation between the HFU and well logs was established using IPSOM Electro-Facies module in order to define the flow units in un-cored wells. The result of this correlation was used to calibrate a Porosity-Permeability relationship for each flow unit.

The next step was examining the clay-type distribution and diagenesis in each flow unit using the petrographic analysis (XRD) results from the core xdata. All factors controlling the permeability can now be represented in hydraulic flow units which are considered as a method of measurement of the reservoir quality. Consequently, property maps were constructed showing the location and continuity of each of the flow units, leading to a more deterministic approach in the well placement process.

Based on this new work methodology, a production cut-off criteria relating the reservoir productivity to both clay minerals presence and percentages was established for multiple wells scenarios. As a result, the development strategy of the field changed from only vertical wells to include horizontal wells as well which proved to be the only economic approach to produce the Illite dominated zones. This paper presents a workflow to provide a representative estimation of permeability in extremely heterogeneous reservoirs especially the ones dominated by complex clay distribution.
A Deep Learning Approach for the Prediction of Oil Formation Volume Factor
Authors: Koffi Itoro Udofort
Published: September 2021

Accurate knowledge of Pressure-Volume-Temperature (PVT) properties is crucial in reservoir and production engineering computational applications. One of these properties is the oil formation volume factor (Bo), which assumes a significant role in calculating some of the prominent petroleum engineering terms and parameters, such as depletion rate, oil in place, reservoir simulation, material balance equation, well testing, reservoir production calculation, etc. These properties are ideally measured experimentally in the laboratory, based on downhole or recommended surface samples. Faster and cheaper methods are important for real-time decision making and empirically developed correlations are used in the prediction of this property.

This work is aimed at developing a more accurate prediction method than the more common methods. The prediction method used is based on a supervised deep neural network to estimate oil formation volume factor at bubble point pressure as a function of gas-oil ratio, gas gravity, specific oil gravity, and reservoir temperature. Deep learning is applied in this paper to address the inaccuracy of empirically derived correlations used for predicting oil formation volume factor. Neural Networks would help us find hidden patterns in the data, which cannot be found otherwise.

A multi-layer neural network was used for the prediction via the anaconda programming environment. Two frameworks for modelling data using deep learning viz: TensorFlow and Keras were utilized, and PVT variables selected as input neurons while employing early stopping which uses a part of our data not fed to the model to test its performance to prevent overfitting. In the modelling process, 2994 dataset retrieved from the Niger Delta region was used. The dataset was randomly divided into three parts of which 60% was used for training, 20% for validation, and 20% for testing.

The result predicted by the network outperformed existing correlations by the statistical parameters used for the same set of field data. The network has a mean average error of 0.05 which is the lowest when compared to the error generated by other correlation models. The predictive capability of this network is found to be higher than existing models, based on the findings of this work.
Application of Cavity Maxwell Garnett Theory in SPR Based Fiber Optic Sensor with Porous Alumina Structure
Authors: - Jyoti , Verma R. K.
Published: September 2021

The present manuscript describes the theoretical understanding of nanoporous alumina based fiber optic sensing structures. The Cavity Maxwell Garnett theory is used to calculate the dielectric functions of the proposed layer. The performance of the proposed sensing structure is evaluated in terms of its sensitivity towards change in the refractive index of the nearby medium. The sharpness of the resonance has also been calculated as an estimation of the performance parameters. It has been observed that the proposed structure is approximately thirteen times more sensitive than the conventional fiber optic sensors. The study has further been extended by replacing the nanolayer of Alumium with the nanolayer of the gold. A comparative study has been provided in terms of the efficiency of the fiber optic probe. The effects of change in pore radius, thickness of the adsorbed medium and shell radius have also been studied.
Eolian chronology reveals causal links between tectonics, climate, and erg generation
Authors: Vainer Shlomy , Matmon Ari , Dor Yoav Ben , Verrecchia Eric , Aumaitre Georges
Published: September 2021

The onset and intensification of eolian activity mark climatic transitions that promote wide-scale aridification, recorded by the generation and preservation of massive sand deposits. Evaluating the impact and implications of such repositories on Earth systems requires knowledge about the timing of their emplacement and the mechanisms responsible for their generation, which remain highly uncertain. Here we provide time constraints for the establishment of the Kalahari Erg, which is the largest continuous body of sand on Earth. We apply cosmogenic nuclide dating of sand from the Kalahari Desert combined with numerical modeling to determine when sand was introduced into the interior of southern Africa. Through the consideration of several scenarios, we show that major events of eolian sand transport and accumulation occurred between ~2.5 and 1 Myr ago. This substantial activity, which significantly altered environmental settings, corresponds to regional, continental, and global scale morphotectonic and climatic changes that contributed to the mass production and widespread dispersion of sand. These changes substantially altered existing habitats, thus constituting a crucial milestone for hominin evolution and migration throughout the African continent during the Pleistocene.
Synergistic Effects of The Hybridization Between Boron-Doped Carbon Quantum Dots And n/n-Type g-C3N4 Homojunction For Boosted Visible-Light Photocatalytic Activity
Authors: Phang Sue Jiun , Lee Jiale , Wong Voon-Loong , Tan Lling-Lling , Chai Siang-Piao
Published: September 2021

Carbon quantum dots (CQDs) are particularly sought after for their highly tailorable photoelectrochemical and optical properties. Simultaneously, graphitic carbon nitride (g-C3N4) has also gained widespread attention due to its suitable band gap energy as well as excellent chemical and thermal stabilities. Herein, a novel boron-doped CQD (BCQD) hybridized g-C3N4 homojunction (CN) nanocomposite was rationally engineered and fabricated via a facile hydrothermal route. The optimal photocatalyst sample, 1-BCQD/CN (with a 1:3 mass ratio of boron to CQD) accomplished a Rhodamine B (RhB) degradation efficiency of 97.0 % within 4 hours under low-powered LED light irradiation. The kinetic rate constant of 1.39 x 10-2 min-1 achieved by the optimum sample was found to be 3.6- and 2.8-folds higher than that of pristine CN and un-doped CQD/CN, respectively. Furthermore, 1-BCQD/CN demonstrated remarkable stability, where it retained close to 99.0% of its initial photocatalytic efficiency after three consecutive cycles. The marked improvement in photocatalytic performance of 1-BCQD/CN was attributed to several concomitant factors such as enhanced electron migration from CN to BCQD, suppressed electron-hole recombination and significantly higher charge density in facilitating charge migration. Based on the scavenging tests, it was revealed that the photogenerated holes (h+), superoxide anions (∙O2–) and hydroxyl radicals (∙OH) were the primary reactive species responsible for the photodegradation process. Overall, the highly efficient 1-BCQD/CN composite with excellent photocatalytic activity could provide a cost-effective and robust means for addressing the increasing concerns over global environmental pollution.
Comprehensive Analysis of miRNA-mRNA Regulatory Network And Potential Drugs In Chronic Chagasic Cardiomyopathy Across Human And Mouse
Authors: Wu Jiahe , Cao Jianlei , Fan Yongzhen , Li Chenze , Hu Xiaorong
Published: September 2021

Background: Chronic chagasic cardiomyopathy (CCC) is the leading cause of heart failure in Latin America and often causes severe inflammation and fibrosis in the heart. Studies on myocardial function and its molecular mechanisms in patients with Chronic chagasic cardiomyopathy are very limited. In order to understand the development and progression of Chronic chagasic cardiomyopathy and find targets for its diagnosis and treatment, the field needs to better understand the exact molecular mechanisms involved in these processes.Methods: The mRNA microarray datasets GSE84796 (human) and GSE24088 (mouse) were obtained from the Gene Expression Omnibus (GEO) database. Homologous genes between the two species were identified using the online database mining tool Biomart, followed by differential expression analysis, gene enrichment analysis and protein-protein interaction (PPI) network construction. Cytohubba plug-in of Cytoscape software was used to identify Hub gene, and miRNet was used to construct the corresponding miRNA-mRNA regulatory network. Furthermore, Comparative Toxicogenomics Database (CTD) was used to identify hub gene-related drugs. Results: A total of 86 homologous genes were significantly differentially expressed in the two datasets, including 73 genes with high expression and 13 genes with low expression. These differentially expressed genes were mainly enriched in the terms of innate immune response, signal transduction, protein binding, Natural killer cell mediated cytotoxicity, Tuberculosis, Chemokine signaling pathway, Chagas disease and PI3K−Akt signaling pathway. The top 10 hub genes LAPTM5, LCP1, HCLS1, CORO1A, CD48, TYROBP, RAC2, ARHGDIB, FERMT3 and NCF4 were identified from the PPI network. A total of 122 miRNAs were identified to target these hub genes and 30 of them regulated two or more hub genes at the same time. Finally, 49 drugs, such as Gentamicins, acetamide, Isotretinoin, Nimesulide, Oxyquinoline, Quercetin and Resveratrol were identified to target these hub genes.Conclusions: In this study, the potential genes associated with Chronic chagasic cardiomyopathy are identified and a miRNA-mRNA regulatory network is constructed. This study explores the molecular mechanisms of Chronic chagasic cardiomyopathy and provides important clues for finding new therapeutic targets.
Geraniol, a Potential Alternative to Antibiotics for Bovine Mastitis Treatment Without Disturbing the Host Microbial Community, Does Not Lead to Drug Residues or Induce Drug Resistance
Authors: Wei Guo , Qiu Min , Pu Zhonghui , Long Nana , Yang Min , Ren Ke , Ning Ruihong , Zhang Siyuan , Lin Lin , Guo Lijuan , Zhang Yanjiao , Deng Jingzhu , Sun Fenghui , Dai Min
Published: September 2021

BackgroundMastitis is one of the important diseases of the dairy cow. Currently, mastitis treatment in dairy cows is mainly based on antibiotics. However, the use of antibiotics causes adverse effects, including drug resistance, drug residues, host-microbiome destruction, and environmental pollution. Geraniol, extracted from Fructus Tsaoko, has demonstrated good antibacterial activity in mouse model. Geraniol and antibiotics were used to treat cows with clinical mastitis to test this possibility of geraniol as a potential alternative to antibiotics for bovine mastitis treatment. The effectiveness of treatment, improvement in inflammatory factors, the influence on microbiome, presence of drug residues, and induction of drug resistance were compared and analyzed.ResultsGeraniol demonstrated a better therapeutic rate than antibiotics on clinical mastitis of cows, with a longer course of treatment. Antibiotics and geraniol significantly reduced the abundance of pathogenic bacteria and restored the microbial community in milk. Meanwhile, geraniol increased the abundance of probiotics in milk. Interestingly, geraniol did not destroy the gut microbial community of cows, whereas antibiotics significantly reduced the diversity and destroyed the community structure of the gut microbiome in cows. Conversely, geraniol increased the diversity of the gut microbiome. Besides, no geraniol residue was detected in the milk four days after treatment discontinuation. However, antibiotic residues were detected in milk at the 7th day after drug withdrawal. In vitro experiments revealed that geraniol did not induce drug resistance in the Escherichia coli strain ATCC25922 after 120 generations of culturing, while antibiotics induced resistance after 10 generations. ConclusionsOur results suggest that geraniol has antibacterial and anti-inflammatory effects similar to antibiotics. Additionally, it retains the structure of the host-microbial community and does not lead to drug residues or induce drug resistance. Therefore, geraniol can be a potential substitute for antibiotics to treat mastitis and be widely used in the dairy industry.
Enhanced oxygen evolution reaction by stacking single-crystalline freestanding SrRuO3
Authors: Wang Qixiang , Liu Huan , He Bin , Qi Ji , Wang Di , Xu Hang , Zhang Nana , Wang Jie , Chen Yanan , Wang Zhihong , Wang Zhengjia , Zheng Limei , Feng Ming , Lü Weiming , Yan Shishen
Published: September 2021

Transition metal oxide thin film has recently become an attractive platform for enhanced catalytic activity and to perceive the fundamental functions of d electron structure and charge transfer processes. Owing to the long-range lattice ordering and accurate stoichiometry, the single-crystalline transition metal oxide thin film enables the mechanism discussion of electrochemistry down to the atomic level. However, it is technically unviable in the fabrication of transition metal oxide thin film with a substantial surface area and strain condition. Here we report the oxygen evolution reaction enhancement by a stack of multilayer SrRuO3 featured with single-crystallinity, flexibility, and stackability, which was achieved from the rigid heterostructure via a water-dissolution of Sr3Al2O6 sacrifice interlayers. The controllable stack of multilayer SrRuO3 and the emergent high-spin state t2g(3↑)eg(1↑) of Ru efficiently enhances the oxygen evolution reaction activity. Our study provides an approach for fine manipulation of single-crystalline freestanding transition metal oxide morphologically, and an efficient strategy aiming at the extreme enhancement of the electrochemically active surface area and strain condition.
WITHDRAWN: Identification and Genetic Analysis of Major Gene ST3GAL4 Related to Serum Alkaline Phosphatase in Chickens
Authors: Tang Hehe , Ma Yanchao , Li Jianzeng , Zhang Zhenzhen , Li Wenting , Huang Hetian , Cai Chunxia , Zhang Lujie , Li Zhuanjian , Jiang Ruirui , Tian Yadong , Li Guoxi , Yan Fengbin , Li Donghua , Zhang Yanhua , Sun Guirong , Li Hong , Liu Xiaojun , Wang Yanbin , Han Ruili , Kang Xiangtao
Published: September 2021

Background: An increasing number of studies have explored disease and growth traits through quantitative trait locus (QTLs) in chickens. Nevertheless, the pathogenic genes underlying the QTL effects remain poorly understood. Alkaline phosphatase (ALP) is a marker of osteoblast maturation and an important indicator of bone metabolism. The change of ALP can reflect the bone metabolism and growth traits of animals to a certain extent. Results: In this study, we identified a SNP site at ST3GAL4 that found by genome-wide association studies (GWAS) in previous studies, and found another 8 SNPs by DNA sequencing. Interestingly, there are 4 SNPs rs475471G>A, rs475533C>T, rs475621A>G, rs475647C>A were completely linked by haplotype analysis, and selected a tag SNP rs475471G>A to analyze the correlation between this SNP and ALP level in Hubbard leg disease population and an F2 chicken resource population produced by Anka and Gushi chickens, and carried out population genetic analysis in 18 chicken breeds. Association analysis showed that this QTL within ST3GAL4 were highly correlated with ALP level, the mutant individuals with genotype AA had the highest ALP level, followed by GA and GG genotypes. The mutant individuals with genotype AA and GA genotype had higher values for body weight (BW), chest width (CW), body slanting length (BSL), pelvis width (PW) at 4-week, the semi-evisceration weight (SEW), evisceration weight (EW) and Leg weight (LW) of AA and GA genotype also higher. The amplification and typing of 4,852 DNA samples from 18 different breeds and the result shown GG genotype mainly existed in egg-type chickens and dual-type chickens, while AA genotype mainly distributed in commercial broilers and F2 resource population. The individuals of AA genotype had the highest ALP and showed better growth performance. This is the first time to report the causal variant of ST3GAL4 gene that located at chromosome 24 related to chicken serum ALP level. Besides, tissue expression analysis used Cobb broiler showed that there were significant differences between different genotypes in spleen and duodenum.Conclusions: This study the first time to determine 9 SNPs within ST3GAL4 were related to ALP in chickens, 4 of them were complete linkage sequence variants, which provide useful information on the mutation of ST3GAL4 and could predict the serum ALP level of chicken early and effectively as a potential molecular breeding marker.
Structure of glycine N-acyltransferase clarifies its catalytic mechanism
Authors: Ebrecht Ana , Badenhorst Christoffel , Read Randy , Opperman Diederik , Dijk Alberdina van
Published: September 2021

Glycine N-acyltransferase (GLYAT; EC 2.3.1.13) is a key enzyme in mammalian homeostasis that has been linked to several pathologies in humans, including cancer. Here we report the first crystal structure of a member of the GLYAT family, and a detailed interpretation of its structure and enzymatic mechanism. This work will aid further studies on GLYAT and its involvement in metabolic diseases and cancer.
Serum-Derived miR-574-5p-Containing Exosomes Contribute to Liver Fibrosis by Activating Hepatic Stellate Cells
Authors: Zhou Xia , Liang Ziyu , Qin Shanyu , Ruan Xianxian , Jiang Haixing
Published: September 2021

Aim: To investigate the association of serum exosomes miR-574-5p with liver fibrosis, and explore the effect and mechanism of serum exosomes on HSC activation.Materials and methods: Using serum samples collected from healthy adults and patients with liver cirrhosis, we extracted human serum exosomes via ultra-high-speed centrifugation, and co-cultured them with hepatic stellate cells (HSCs) line LX2.LX-2-mediated intake of human serum exosomes was examined by confocal microscopy. To induce liver fibrosis, we administered 20% CCl4 to mice intraperitoneally and adopted an exoEasy MIDI kit to extract serum exosomes.Liver fibrosis-related molecules were determined via qRT-PCR, Western blot, Masson staining, and Immunohistochemical staining.Results: Significantly high miR-574-5p levels were expressed in serum exosomes and were positively correlated with the expression of miR-574-5p, collagen deposition, and α-SMA expression in liver tissues of mice during liver fibrosis. Compared to healthy subjects, serum exosomes from cirrhosis patients were associated with higher expression of miR-574-5p, α-SMA, and COL1A1 in LX-2. miR-574-5p mimic promoted the expression of α-SMA and COL1A1 mRNA and protein in LX-2, whereas miR-574-5p inhibitor exerted no effect.Conclusion: This article demonstrates that miR-574-5p expression in serum exosomes is positively correlated with collagen deposition and HSC activation in liver tissues during liver fibrosis.Serum exosomes potentially activate HSC through the transfer of miR-574-5p to HSC during liver fibrosis.
HELZ2 Promotes K63-Linked Polyubiquitination of c-Myc to Induce Retinoblastoma Tumorigenesis
Authors: Dai Hanjun , ZENG wen , ZENG WEIJUAN , YAN MING , jiang ping , LI ying , zhang wei , ke min
Published: September 2021

Retinoblastoma is a rare ocular tumor in children that originates in the retina. Several core transcriptional regulators maintain the expansion of retinoblastoma tumors, including c-Myc. Here, we demonstrated that Helicase with zinc finger domain 2 (HELZ2) promoted retinoblastoma tumorigenesis by targeting c-Myc. HELZ2-deficient inhibited retinoblastoma cell proliferation, whereas overexpression of HELZ2 promoted retinoblastoma cell proliferation. In addition, high levels of HELZ2 promoted xenograft retinoblastoma tumorigenesis and inhibited animal survival. Mechanistically, HELZ2 interacted with c-Myc and promoted its K63-linked polyubiquitination. We indicated that HELZ2 promoted the interaction between E3 ubiquitin ligase HUWE1 and c-Myc, and HELZ2-mediated K63-linked polyubiquitination and activation of c-Myc were dependent on HUWE1. Taken together, HELZ2 plays a critical role in the regulation of retinoblastoma tumorigenesis by enhancing the activity of c-Myc.
Application of The PRECEDE -PROCEED Model in Prevention of Brucellosis Focused On Livestock Vaccination Process
Authors: Bahadori Farhad , Ghofranipour Fazlollah , Zarei Fatemeh , Ziaei Reza , Ghaffarifar Saeideh
Published: September 2021

Background
This article reports the steps of an educational intervention, which is designed to change livestock breeders’ preventive behavior in terms of vaccinating their livestock against brucellosis. The study has been conducted in a rural area in a country with the second highest brucellosis prevalence in the world.
Methods
In a quasi-experimental study and applying PRECEDE-PROCEED model, 45 livestock breeders were trained through basket method, accompanied with constructive feedback from researchers and peers and a brief interactive lecture at the end. The livestock breeders’ awareness, attitude and practice level in the intervention group was compared with those of other 45 livestock breeders in a control group, one and six months after the intervention. The presence of anti-brucellosis antibodies in livestock’s blood was compared in groups and considered as the outcome measure of the intervention.
Results
Immediately and one month after the intervention, the mean scores of knowledge, awareness and practice of livestock breeders in the intervention group were significantly higher. Six months after the intervention, the results of the Rose Bengal tests were positive in more livestock in the intervention group compared to the animals in the control group.
Conclusion
The model-driven educational intervention could significantly increase livestock breeders' awareness, attitude and practice regarding prevention of brucellosis and vaccination of their livestock against brucellosis; however, a period of non-continuous reinforcement and gradual reduction of the number of the reinforcements by health educator workers is recommended in order to increase the maintenance of the learnt behavior.
Trial registration:
Conducting this study was registered at Iranian Registry of Clinical Trials (IRCT20180304038945N1). Registered 24 December 2018(https://www.irct.ir/trial/29996).The proposal was registered before enrollment of the first participant.
Topological and Enzymatic Analysis of Human Alg2 Mannosyltransferase
Authors: Xiang Meng-Hai , Xu Xin-Xin , Wang Chun-Di , Chen Shuai , Xu Si , Xu Xiang-Yang , Dean Neta , Wang Ning , Gao Xiao-Dong
Published: September 2021

N-glycosylation starts with the biosynthesis of lipid-linked oligosaccharide (LLO) on the endoplasmic reticulum. Alg2 mannosyltransferase adds both the α1,3- and α1,6-Man onto ManGlcNAc2-pyrophosphate-dolichol (M1Gn2-PDol) in either order to generate the branched M3Gn2-PDol product. The well-studied yeast Alg2 interacts with ER membrane through four hydrophobic domains. Unexpectedly, we show that Alg2 structure has diverged significantly between yeast and humans. Human Alg2 (hAlg2) associates with the ER via a single membrane-binding domain and is markedly more stable in vitro. These properties were exploited to develop an LC-MS quantitative kinetic assay for studying purified hAlg2. Under physiological conditions, hAlg2 prefers to transfer α1,3-Man on to M1Gn2 before adding the α1,6-Man. However, this bias is altered by an excess of GDP-Man donor or an increased level of M1Gn2 substrate, both of which trigger production of the M2Gn2 (α-1,6)-PDol. These results suggest that Alg2 may regulate the LLO biosynthetic pathway by controlling accumulation of M2Gn2 (α-1,6) intermediate.
Biodegradable Star-shaped Poly(Lactic Acid): Synthesis, Characterization and Its Reaction Kinetics
Authors: He Jing , Yu Tao , Yang Weidong , Li Yan
Published: September 2021

Biodegradable four-arm star-shaped poly(lactic acid) (4sPLA) was synthesized from L-Lactic acid ( L-LA) and pentaerythritol (PENTA), and the polymerization kinetics was studied. The effects of reaction time, reaction temperature and molar ratio on the polymerization of 4sPLA were discussed. The molecular structure of 4sPLA was characterized by Fourier transform infrared spectroscopy (FTIR) and 1H nuclear magnetic resonance spectra ( 1 H-NMR). The results showed that the optimum reaction conditions were as follows: the molar ratio of L-LA to PENTA was 12:1, and the polymerization reaction occurred at 160 ℃ for 5 h. Gel permeation chromatography (GPC) method was used to determine the polymerization kinetics of 4sPLA consistent with the first-order reaction kinetics.
Protist.Guru: A Comparative Transcriptomics Database for the Protist Kingdom
Authors: Villanueva Erielle Marie Fajardo , Lim Peng Ken , Lim Jolyn Jia Jia , Lim ShanChun , Lau Pei Yi , Koh Kenny , Tan Emmanuel , Kairon Ryanjit Singh , See Wei An , Liao Jian Xiang , Hee Ker Min , Vijay Varsheni , Maitra Ishani , Boon Chong Jun , Fo Kevin , Wang Yee Tat , Jaya Ryan , Hew Li Anne , Lim Yong Yee , Lee Wei Quan , Lee Zhi Qi , Foo Herman , Santos Adriana Lopes dos , Mutwil Marek
Published: September 2021

Summary: During the last few decades, the study of microbial ecology has been enabled by molecular and genomic data. DNA sequencing has revealed the surprising extent of microbial diversity and how microbial processes run global ecosystems. However, significant gaps in our understanding of the microbial world remain, and one example is that microbial eukaryotes, or protists, are still neglected. To address this gap, we used gene expression data from 15 distinct protist species to create protist.guru: an online database equipped with tools for identifying functional co-expression networks, gene families, and enriched gene clusters. Here, we show how our database can be used to reveal genes involved in essential pathways, such as the synthesis of secondary carotenoids in Haematococcus lacustris. We expect protist.guru to serve as a valuable resource for protistologists, as well as a catalyst for discoveries and new insights into the biological processes of microbial eukaryotes. Availability: The database and co-expression networks are freely available from http://protist.guru/. The expression matrices and sample annotations are found in the supplementary data.
Rheum to Diagnosis: A Mixed Methods Study to Uncover Impediments to Accurate Diagnosis of Nonradiographic Axial Spondyloarthritis in the United States
Authors: Kiwalkar Sonam , Howard Richard , Choi Dongseok , Deodhar Atul
Published: September 2021

BackgroundDelayed diagnosis of axial spondyloarthritis (axSpA) is well documented, but little is known about the distinct diagnostic journey and impediments for US patients with nonradiographic axSpA (nr-axSpA).MethodsInterviews of adults with rheumatologist-diagnosed nr-axSpA and of rheumatologists explored the diagnostic journey and barriers to diagnosis. Emerging themes were further explored in an online patient survey. Patients were recruited through Spondylitis Association of America outreach and patient panels. ResultsInterviews were conducted with 25 patients (mean age, 45 years; 80% female) and 16 rheumatologists. Survey responses from 186 eligible patients (median age, 40 years; 67% female) were analyzed. Among surveyed patients, median time from symptom onset to nr-axSpA was 3.25 years. In multivariable analysis, delayed diagnosis was significantly more likely for women and people in rural areas. Most patients consulted ≥4 different types of healthcare providers (HCPs) before seeing a rheumatologist and consulted ≥2 rheumatologists before nr-axSpA diagnosis. Identified impediments to timely diagnosis included the insidious onset of bothersome but tolerable chronic pain; episodic rather than persistent symptom patterns that seemed related to activity; symptoms other than chronic lumbosacral back pain that were dominant and required medical consultation; and widespread unfamiliarity with and misperceptions about nr-axSpA among frontline HCPs, radiologists, and rheumatologists. ConclusionsDelayed nr-axSpA diagnosis is common and reflects HCP knowledge gaps as well as frequent patient presentation with dominant nonaxial symptoms. Targeted HCP education, further research into early disease patterns, and interventions sensitive to the broader spectrum of nr-axSpA manifestations are needed to improve timely diagnosis. Trial RegistrationNot applicable.