bluuebunny/crossref_metadata_2025 huggingface dataset:
Securing Zonal Isolation Across a Highly Depleted GoM Deep Water Reservoir
Authors: Esquitin Yosafat , Chima Chima , Vasques Ricardo , Hazel Paul , Schwanitz Brian
Published: September 2021

Effective zonal isolation within a layered reservoir in the Gulf of Mexico is a necessity to meet regulations for stacked reservoirs and to maximize total recoverables. Effective zonal isolation also ensures maximum production is achieved via a high-pressure proppant fracture treatment. A primary cement operation of a 10 1/8" production liner (within a 12 ¼" drilled hole section) was challenging due to a combination of high equivalent circulation density (ECD) and potential losses across a layered GOM reservoir. One layer had potential and significant depletion up to 8,000 psi. Critical well parameter considerations were: maintaining the liner burst of 18,200 psi, maximizing rotation and reciprocation capability of the liner, minimizing the impact on circulation and ECD, and ensuring compatibility with the mud systems.

Following careful job planning, including the analysis of caliper data from logging while drilling (LWD) for the optimum placement, two metal expandable packers (MEPs) were installed on the 10 1/8" liner. The MEPs were positioned to straddle the highly depleted layer (one above and one below) in the 12 ¼" open hole section. The liner was deployed, and the cement operation was executed with minimal ECD impact from the inclusion of the MEPs. Surface pressure was applied to create sufficient differential pressure across the 10 1/8" liner wall to hydraulically expand the MEPs quickly under full surface control.

This paper covers the qualification, planning, and deployment of MEPs to provide cement assurance (CA) for zonal isolation and improve the effectiveness of contingency cement squeezes. Though this technology has been used in other regions for several years, this was the first deployment in the Gulf of Mexico (GOM). The solution improved the probability of success of the primary cement job, negating the requirement for a remedial cement squeeze. The decision to run MEPs was based on the estimated cost savings of 3.5 million USD for remedial squeeze operations, a value proposition that did not account for the net present value (NPV) gain, due to improved fracture placement, compared to the case of poor cement isolation.
Relationship between Residual Saturations and Wettability using Pore-Network Modeling
Authors: Purswani Prakash , Johns Russell T. , Karpyn Zuleima T.
Published: September 2021

The relationship between residual saturation and wettability is critical for modeling enhanced oil recovery (EOR) processes. The wetting state of a core is often quantified through Amott indices, which are estimated from the ratio of the saturation fraction that flows spontaneously to the total saturation change that occurs due to spontaneous flow and forced injection. Coreflooding experiments have shown that residual oil saturation trends against wettability indices typically show a minimum around mixed-wet conditions. Amott indices, however, provides an average measure of wettability (contact angle), which are intrinsically dependent on a variety of factors such as the initial oil saturation, aging conditions, etc. Thus, the use of Amott indices could potentially cloud the observed trends of residual saturation with wettability.

Using pore network modeling (PNM), we show that residual oil saturation varies monotonically with the contact angle, which is a direct measure of wettability. That is, for fixed initial oil saturation, the residual oil saturation decreases monotonically as the reservoir becomes more water-wet (decreasing contact angle). Further, calculation of Amott indices for the PNM data sets show that a plot of the residual oil saturation versus Amott indices also shows this monotonic trend, but only if the initial oil saturation is kept fixed. Thus, for the cases presented here, we show that there is no minimum residual saturation at mixed-wet conditions as wettability changes. This can have important implications for low salinity waterflooding or other EOR processes where wettability is altered.
Machine Learning Predictive Models to Estimate the UCS and Tensile Strength of Rocks in Bakken Field
Authors: Chemmakh Abderraouf
Published: September 2021

Uniaxial Compressive Strength (UCS) and Tensile Strength (TS) are among the essential rock parameters required and determined for rock mechanical studies in Petroleum Engineering. However, the determination of such parameters requires some laboratory experiments, which may be time-consuming and costly at the same time. In order to estimate these parameters efficiently and in a short period, some mathematical tools have been used by different researchers. When regression tools proved to give good results only in the limited range of data used, machine learning methods proved to be very accurate in generating models that can cover a wide range of data. In this study, two machine learning models were used to predict the UCS and TS, Support Vector Regression optimized by Genetic Algorithm (GA-SVR) and Artificial Neural Networks (ANNs).

The results were discussed for both uniaxial compressive strength and tensile strength in terms of coefficient of determination R2, root mean squared error (RMSE) and mean average error (MAE). First, for the case of UCS, values of 0.99 and 0.99, values of 3.41 and 2.9 and values of 2.43 and 1.9 were obtained for R2, RMSE and MAE for the ANN and GA-SVR, respectively. Second, for the TS, the same analogy was followed, a coefficient R2 of 0.99 and 0.99, RMSE values of 0.41 and 0.45 and MAE values of 0.30 and 0.39 were obtained for ANNs and GA-SVR, respectively. The next step was to assess these models on a different dataset consisting of data obtained from Bakken Field in Williston Basin, North Dakota, United States. The models showed excellent results comparing to the correlations they were compared with, outperforming them in terms of R2, RMSE and MAE, giving the following results for ANN and SVR respectively, R2 of 0.93, 0.92, RMSE of 9.54, 11.22 and MAE of 7.28, 9.24. The resultant conclusion of this work is that the use of machine learning algorithms can generate universal models which reduce the time and effort to estimate some complex parameters such as UCS and Tensile Strength.
Minimum Miscibility Pressure of Gas Injection in Unconventional Reservoirs
Authors: Yang Gang
Published: September 2021

Unconvnetional reservoirs are predominantly consisted of nanoscale pores. The strong confinement effect within nanopores imposes significant deviations to the confined fluid phase behavior. Minimum miscibility pressure (MMP) in unconventional reservoirs, as a parameter highly related to the phase behavior of confined fluids, is inevitably affected by the nanoscale confinement. The objective of this work is to investigate the impact of nanoscale confinement on MMP of unconventional reservoir fluids and to recognize a reliable theoretical approach to determine the MMP values in unconventional reservoirs.

A modified Peng-Robinson equation of state (PR EOS) applicable for confined fluid characterization is applied to perform the EOS simulation of the vanishing interfacial tension (VIT) experiments. The MMP of a binary mixture at bulk and 50 nm are obtained via the VIT simulation. Meanwhile, the multiple mixing cell (MMC) algorithm coupled with the modified PR EOS is applied to compute the MMP for the same binary system. Comparison of the calculated results to the experimental values recognize that the MMC approach has higher accuracy in determining the MMP of confined fluid systems. Moreover, this approach is then applied to predict the MMP values of both Bakken and Eagle Ford oil at different pore sizes with various injected gases. Results demonstrate that the nanoscale confinement causes drastic suppression to the MMP of unconventional reservoir fluids and the suppression rate increases with decreasing pore size. The drastic suppression of MMP is highly favorable for the miscible gas injection EOR in unconventional reservoirs.
Utilizing Data-Driven Models to Predict Brittleness in Tuscaloosa Marine Shale: A Machine Learning Approach
Authors: Ahmadov Jamal
Published: September 2021

The Tuscaloosa Marine Shale (TMS) formation is a clay- and liquid-rich emerging shale play across central Louisiana and southwest Mississippi with recoverable resources of 1.5 billion barrels of oil and 4.6 trillion cubic feet of gas. The formation poses numerous challenges due to its high average clay content (50 wt%) and rapidly changing mineralogy, making the selection of fracturing candidates a difficult task. While brittleness plays an important role in screening potential intervals for hydraulic fracturing, typical brittleness estimation methods require the use of geomechanical and mineralogical properties from costly laboratory tests. Machine Learning (ML) can be employed to generate synthetic brittleness logs and therefore, may serve as an inexpensive and fast alternative to the current techniques. In this paper, we propose the use of machine learning to predict the brittleness index of Tuscaloosa Marine Shale from conventional well logs.

We trained ML models on a dataset containing conventional and brittleness index logs from 8 wells. The latter were estimated either from geomechanical logs or log-derived mineralogy. Moreover, to ensure mechanical data reliability, dynamic-to-static conversion ratios were applied to Young's modulus and Poisson's ratio. The predictor features included neutron porosity, density and compressional slowness logs to account for the petrophysical and mineralogical character of TMS.

The brittleness index was predicted using algorithms such as Linear, Ridge and Lasso Regression, K-Nearest Neighbors, Support Vector Machine (SVM), Decision Tree, Random Forest, AdaBoost and Gradient Boosting. Models were shortlisted based on the Root Mean Square Error (RMSE) value and fine-tuned using the Grid Search method with a specific set of hyperparameters for each model. Overall, Gradient Boosting and Random Forest outperformed other algorithms and showed an average error reduction of 5 %, a normalized RMSE of 0.06 and a R-squared value of 0.89. The Gradient Boosting was chosen to evaluate the test set and successfully predicted the brittleness index with a normalized RMSE of 0.07 and R-squared value of 0.83.

This paper presents the practical use of machine learning to evaluate brittleness in a cost and time effective manner and can further provide valuable insights into the optimization of completion in TMS. The proposed ML model can be used as a tool for initial screening of fracturing candidates and selection of fracturing intervals in other clay-rich and heterogeneous shale formations.
A Unified Parameter to Represent Reservoir Heterogeneity
Authors: Ramabhadra Agastya Nandana
Published: September 2021

We aim to find a universal method and/or parameter to quantify impact of overall heterogeneity on waterflood performance. For this purpose, we combined the Lorenz coefficient, horizontal permeability to vertical permeability ratio, and thief zone permeability to average permeability ratio, with a radar chart. The area of the radar chart serves as a single parameter to rank reservoirs according to heterogeneity, and correlates to waterflood performance.

The parameters investigated are vertical and horizontal permeability. Average porosity, initial water saturation, and initial diagonal pressure ratio are kept constant. Computer based experiments are used over the course of this entire research. We conducted permeability studies that demonstrate the effects of thief zones and crossflow. After normalizing these parameters into a number between 0 and 1, we then plot them on a radar chart.

A reservoir's overall degree of heterogeneity can be inferred using the radar chart area procedure discussed in this study. In general, our simulations illustrate that the larger the radar chart area, the more heterogenous the reservoir is, which in turn yields higher water cut trends and lower recovery factors. Computer simulations done during this study also show that the higher the Lorenz coefficient, the higher the probability of a thief zone to exist. Simulations done to study crossflow also show certain trends with respect to under tonguing and radar chart area.
Unlocking Field Potential of Mature Fields Using Hybrid Fuzzy Modelling and Kriging Method
Authors: Surana Saransh
Published: September 2021

Reservoir uncertainties, high water cut, completion integrity along with declining production are the major challenges of a mature field. These integrated with dying facilities and poor field production are key issues that each oil and gas company is facing these days. Arresting production decline is an inevitable objective, but with the existing techniques/steps involved, it becomes a cumbersome and exorbitant affair for the operators to meet their requirements. In addition, incompetent and flawed well data makes it more challenging to analyze mature fields. Although flow rate data is the most easily accessible data for mature fields, the absence of pressure data (flowing bottom-hole or wellhead pressure) remains a big obstacle for the application of conventional production enhancement and well screening strategies for most of the mature fields.

A real-time optimization tool is thus constructed by developing a hybrid modelling technique that encapsulates Kriging and Fuzzy Logic to account for the imprecisions and uncertainties involved while identification of subsurface locations for production optimization of a mature field using only production data. The data from the existing wells in the field is used to generate a membership function based on its historical performance and productivity, thereby generating a spatial map of prospective areas, where secondary development operations can be taken up for production optimization.
Inflammatory Bowel Disease in Pregnancy: Case Series with Review of Literature
Authors: Lenin Audrin , Ninan George Abraham , Vijayaselvi Reeta , Rathore Swati , Jasmine Sudha
Published: September 2021

Background:Inflammatory bowel disease(IBD) affects women in their reproductive years with severe disease associated with maternal morbidity and adverse fetal outcomesMethodology and Results:We report our experience of managing pregnant women with IBD in South India. Of the five patients with IBD and 8 pregnancies, 2 presented with active severe disease during pregnancy and were treated with steroids and azathioprine. One developed chorioamnionitis and the other metabolic complications. All except 1 pregnancy required operative delivery by LSCS or instrumental delivery. The mean GA at delivery was 38+5 weeks with a mean birth weight of 2.93kg.Conclusion:Pregnancy outcomes in IBD are dependent on the disease activity status at conception. Diagnosis of IBD in pregnancy is a challenge as full length colonoscopy and CT imaging is not feasible. Chorioamnionitis is a complication associated with IBD, probably due to immunosuppressive drugs. There were no neonatal complications.
Analytical Study for Chlorpyrifos Breakdown Derivatives Qualification After Silver Vanadate (Agvo3) Nanoparticles Fragmentation Reaction
Authors: Ghoniem Islam R. , Elmarsafy Ashraf M. , Amer Mohamed A. , Gammal Hassan A. El- , Aly Mohamed M. Abo , Sayed Mostafa A.
Published: September 2021

The use of pesticides in agriculture has become one of the basic necessities to meet the world's food requirements as a result of the continuous population increase. But sometimes the use of some of these pesticides in large quantities and in high concentrations poses a great danger to the environment and then to humans. Through weather factors, pesticides are transferred to the water and then harm aquatic organisms, which leads to a direct impact and harm to the fish wealth. Monitoring these compounds in the environment requires a large cost of time and money to ensure food safety. Therefore, a new method was used in this study in an attempt to get rid of these compounds in water. The silver vanadate nanoparticles (AgVO3) were synthesized using a novel method in an attempt to eliminate different groups of pesticides that had been detected in Egyptian agricultural crops and water. The effect of 0.1 g of AgVO3 nanoparticles were found on three compounds: chlorpyrifos, dimethoate and malathion. Where a concentration of these compounds, which is 0.5 mg / kg, was used and it was estimated using Exion HPLC coupled with Sciex Qtrap API 6500 + LC-MS/MS System. After 15 minutes of treatment with 0.1 g of AgVO3 nanoparticles, these compounds were undetectable on the device's chromatogram, which is regarded a short period in Affecting these compounds and changing their nature in an attempt to get rid of them. Determination of chlorpyrifos breakdown products by using mass scan of Qtrap API 6500 + LC-MS/MS System and Thermo Scientific Q Exactive Focus Orbitrap LC-MS/MS System was investigated. Supported AgVO3 NPs, according to the study, could be used in long-term environmental remediation because they can be used in aqueous solutions at room temperature without the need for additional stimulus such as UV light.
Application of Response Surface Methodology for Optimization of Biodiesel Production from Microalgae Through Nanocatalytic Transesterification Process.
Authors: Mittal Vaishali , Ghosh Uttam Kumar
Published: September 2021

Production of biodiesel from microalgae is gaining popularity since it does not compromise food security or the global economy. This article reports biodiesel production with Spirulina microalgae through nanocatalytic transesterification process. The nanocatalyst calcium methoxide Ca(OCH3)2 was synthesized using wet impregnation method and utilized to carry out the transesterification process. The nanocatalyst was characterized to evaluate its structural and spectral characteristics using different characterization techniques such as Thermogravimetric analysis (TGA), X-ray diffraction (XRD), Scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FT-IR), and Brunaeur-Emmett-Teller(BET) measurement for surface area. The result demonstrates that calcium methoxide Ca(OCH3)2 possesses a high catalytic activity compared to a heterogeneous catalyst such as calcium oxide (CaO). The impact of several process parameters such as reaction temperature, the molar ratio of methanol to oil, catalyst concentration, and reaction time used in the transesterification process was optimized by employing central composite design(CCD) based response surface methodology(RSM). The polynomial regression equation of second order was obtained for methyl esters. The model projected a 99% fatty acid methyl esters (FAME) yield for optimal process parameters of reaction time 3hrs,3 wt.% of Ca(OCH3)2 catalyst loading, 80°C reaction temperature, and 30:1 methanol to oil molar ratio.
Performance Model for Factory Automation in 5G Networks
Authors: wang jiao , Weitzen Jay , Bayat Oguz , Sevindik Volkan , Li Mingzhe
Published: September 2021

The fifth generation (5G) of mobile networks is emerging as a key enabler of modern factory automation (FA) applications that ensure timely and reliable data exchange between network components. Network slicing (NS), which shares an underlying infrastructure with different applications and ensures application isolation, is the key 5G technology to support the diverse quality of service requirements of modern FA applications. In this article, an end-to-end NS solution is proposed for FA applications in a 5G network. Regression approaches are used to construct a performance model for each slice to map the service level agreement to the network attributes. Interference coordination approaches for switched beam systems are proposed to optimize radio access network performance models. A case study of a non-public network is used to show the proposed NS approach.
Hijacking of transcriptional condensates by endogenous retroviruses
Authors: Asimi Vahid , Hetzel Sara , Kumar Abhishek Sampath , Niskanen Henri , Riemenschneider Christina , Naderi Julian , Fasching Nina , Popitsch Niko , Kretzmer Helene , Smith Zachary , Walther Maria , Meierhofer David , Wittler Lars , Buschow René , Timmermann Bernd , Ameres Stefan , Meissner Alexander , Hnisz Denes
Published: September 2021

Endogenous retroviruses (ERVs) comprise ~10% of mammalian genomes, and ERVs are repressed by multiple cellular mechanisms including heterochromatin, DNA methylation, and methylation of their RNA transcripts 1-13. Although the vast majority of ERVs in mammals are incapable of retrotransposition, ERV de-repression during early development is associated with embryonic lethality 14-16, suggesting that ERV transcription or RNA transcripts may underlie essentiality of ERV repression. Here we report that rapid and selective degradation of the TRIM28 heterochromatin adapter protein in murine embryonic stem cells triggers dissociation of transcriptional condensates from loci encoding super-enhancer -driven pluripotency genes, and association of transcriptional condensates with transcribed ERV loci. Knockdown of ERV RNA or forced expression of super-enhancer -enriched transcription factors rescued condensate localization at super-enhancers in TRIM28-degraded cells. In a biochemical reconstitution system, ERV RNA facilitated phase separation of RNA Polymerase II, and partitioning of NFY and Mediator into heterotypic droplets, suggesting a mechanistic basis for the association of transcriptional condensates with ERVs. Using a zygotic perturbation platform, we found that timing and amount of ERV transcription correlate with the onset of lethality, and that loss of TRIM28 leads to specific depletion of pluripotent lineages in mouse embryos. We propose that retrotransposons contribute to the genomic distribution of nuclear condensates, and that coding and non-coding nascent RNAs may facilitate “hijacking” of transcriptional condensates in various developmental and disease contexts.
On Farm Varietal Diversity and Prevalence of Aspergillus Contamination of Groundnut (Arachis hypogaea L.) in Major Production Areas of Oromia Region, Ethiopia
Authors: Abebe Dereje Dunfa , Ruelle Morgan , Chimdessa Meseret , Tewolde-Berhan Sarah
Published: September 2021

Background: Groundnut is one of the most valuable cash crops and food sources in low lands of Ethiopia. In spite of its food and economic importance, very few studies have been conducted yet on the factors that influence groundnut production includingaflatoxigenic fungi in different socio-ecological conditions. Therefore, this study aimed ati) assessing groundnut varietal diversity ii) to determine the existing use values and management practices iii) to isolate and determine the prevalence of Aspergillus species associated with groundnut seed.Methods: Field data were collected using structured and semi-structured interviews from 144 general informants and 24 key-informants. 88 groundnut seed samples were collected from farmers’ fields for Aspergillus species isolation. Diversity of groundnut was analyzed using the Shannon diversity index. Frequency of Aspergillus contamination was determined using plate counting methods.Results: In the study areas,six varieties were grown with varying distribution. Shannon diversity indices ranged from 0.20 to 1.27in warm sub-humid lowland and warm moist lowland agro-ecological zones, respectively. Of the four varieties observed in East Hararghe, oldhale was the most commonly grown variety (66% of groundnut growers), whereas farmers interviewed in East Wellega zone grow bure variety (87% of growers), due to greater drought tolerance and higher yields relative to other varieties. Results of the fungal species analysis showed infestation of groundnut seeds by A.niger, A. flavus, A. prasaticus and A. ochraceous. Of the four Aspergillus species, A. nigerand A. flavus were the most prevalent, with frequency ranging from 17.8 to 37.5% and 14.4 to 32.5%, respectively.However, when we compareinfection rates among varieties, we did not find statistically significant differences in the infection rates of different varieties collected from similar agroecology of the study area.Conclusion: Different varieties of groundnut weregrown with varying distribution based on the farmers’ preference criteria in different socio-ecological zones of the study areas. Although these varieties vary in terms of morphological features and disease resistance, there is not sufficient evidence to conclude they are differentially resistant to Aspergillus infection. Therefore, further breeding for more varieties using farmer selection criteria in mind and research identify field management measures against Aspergillus will further increase groundnut production and hence income for resource poor farmers
Fusarium Oxysporum Disrupts Microbiome-Metabolome Networks in Arabidopsis Thaliana Roots
Authors: Kudjordjie Enoch Narh , Hooshmand Kourosh , Sapkota Rumakanta , Fomsgaard Inge S. , Nicolaisen Mogens
Published: September 2021

BackgroundAlthough it is well established that plant metabolomes mediate microbiome assembly, the question of how metabolome-microbiome interactions may prevent pathogen invasion remains to be answered. To address this question, we studied microbiome and metabolome profiles of two Arabidopsis thaliana accessions, Columbia-0 (Col-0) and Landsberg erecta (Ler-0) with differential resistance profiles to the fungal pathogen Fusarium oxysporum f.sp. mathioli (FOM). We used amplicon sequencing to characterize bacterial (16S) and fungal (ITS2) communities, and we used targeted metabolite analysis across 5 stages of FOM host progression. ResultsWe found that microbiome and metabolome profiles were markedly altered in FOM-inoculated and non-inoculated samples of resistant Col-0 and susceptible Ler-0. Co-occurrence network analysis revealed robust microbial networks in the resistant Col-0 compared to the susceptible Ler-0, during FOM infection. Specific metabolites and microbial OTUs (including indicator and hub OTUs) correlated in both non-inoculated and inoculated Col-0 and Ler-0. The glucosinolates 4-hydroxyglucobrassicin, neoglucobrassicin and indole-3 carbinol, but also phenolic compounds were active in structuring the A. thaliana-microbiome. ConclusionsOur results highlight the interactive effects of host resistance and its associated microbiota on Fusarium infection and progression. These findings shed significant insights into plant inter-omics dynamics during pathogen invasion and could possibly facilitate the exploitation of microbiomes for plant disease control.
Myogenic differentiation potential of chicken mesenchymal stem cells from bone marrow
Authors: Zhou Zhen , Zhao Changbin , Cai Bolin , Ma Manting , Kong Shaofen , Zhang Jing , Zhang Xiquan , Nie Qinghua
Published: September 2021

Background: Mesenchymal stem cells (MSCs) have the potential to multilineage differentiation, which can be used for a good model to provide critical insight of chicken muscle development. Differential adhesion method is one of the commonest methods to isolate MSCs based on the ability of plastic adhesion. 5-azacytidine (5-Aza), dexamethasone (DXMS), hydrocortisone (HC) and horse serum had been proved the potential to induce the myogenic differentiation of MSCs. However, the myogenic differentiation of MSCs is still poorly understood in chicken. In present study, we isolated chicken mesenchymal stem cells (cMSCs) from bone using 4-hour differential adhesion method and analyzed the myogenic effect of cMSCs treated with different method based on 5-Aza, DXMS, HC and horse serum.Results: cMSCs isolated by 4-hour differential adhesion method expressed MSCs special surface markers and presented normal growth characteristic. cMSCs showed great potential of myogenic differentiation by the treatment of 5-Aza and horse serum. RNA-sequence, GO and KGEE enrichment analysis revealed that this effect might be based on demethylation of 5-Aza and ECM-receptor interaction, focal adhesion, PI3K-Akt, p53, TGF-beta signaling pathways. Moreover, DXMS, HC and horse serum also presented potential of myogenic differentiation, but the effect was not as good as 5-Aza and horse serum method.Conclusions: cMSCs showed potential of myogenic differentiation by the treatment of 5-Aza and horse serum or DXMS, HC and horse serum.
Evaluation of Invasive and Molecular Methods in the Diagnosis of Helicobacter Pylori From Gastric Biopsies of Sudanese Patients. A Comparative Approach
Authors: Elnosh Maram M. , Altayb Hisham N. , Hamedelnil Yousif Fadalla , Elshareef Wafa A. , Abugrain Aliaa Yahia , Osman Esraa Hassan , Albasha Aalaa Mahgoub , Abdelhamid Abdelhamid Gezouli , Moglad Ehssan H. , Ismail Ahmed Elhaj
Published: September 2021

The continuous rise in the number of patients suffering from Helicobacter pylori is probably due to the changes in modern life. Nowadays patients suffering from gastrointestinal problems are diagnosed through invasive and noninvasive techniques. The choice of a diagnostic test is influenced by factors such as the tests' sensitivity and specificity, the clinical conditions, and the cost-effectiveness of the testing strategy. This study aimed to compare molecular detection methods of H. pylori by polymerase chain reaction (PCR) targeting the 16S rRNA, ureA and glmM genes with an invasive histopathological technique. A total of 290 patients from various hospitals in Khartoum State were recruited in this study between March 2018 and January 2020. Two gastric biopsies were collected from each patient for PCR and histopathology.A total of 103 (35.5%) samples were positive by histopathological examination, 88 (30.3%) by 16SrRNA, 39 (13.4%) by glmM gene, and 56 (19.3%) by ureA gene. The highest sensitivity was observed in 16SrRNA (46.6%), followed by ureA (35%), and glmM (24.3%). While the best specificity was observed in glmM gene (92.5%), followed by ureA (89.3%) and 16SrRNA (78.6%). In conclusion, the PCR test targeting the16SrRNA gene exhibited the best results for molecular detection of H. pylori compared to other genes.
Bioinformatic Analysis of Diagnosis, Targeted Therapeutic Values and Potential Regulatory Network of FOXF1 in Ovarian Cancer
Authors: Zhang Xiang , Chen Jianhong , Wang Fangfang , Zhang Meng , Liu Jiping
Published: September 2021

Background: FOXF1 acts a crucial part to tumor initiation and progression. In this study, we aimed to analyzed FOXF1 in ovarian cancer from different databases which showed diagnosis and targeted therapeutic values.Results: The expression of FOXF1 in ovarian cancer tissue was markedly lower than that in normal tissue. Among different tumor subgroups, FOXF1 expression was conspicuously lower in higher grade stage. Additionally, FOXF1 expression and genetic variations were significantly correlated with various immune infiltrating cells. Altogether, 2594 co-expressed genes evidently pertinent to FOXF1. These genes were correlated with cell adhesion, NADH dehydrogenase complex and cytokine binding in results of enrichment analysis. In addition, FOXF1 was associated with gene networks regulated by PRKG1, miR-151, and SRF respectively. CMap analysis screened several potential small molecules for ovarian cancer treatment.Conclusions: FOXF1 has been shown to be a vital biomarker for the diagnosis of ovarian cancer and the immune infiltrating levels. The small molecules screened here supply rationale for new drug development for ovarian cancer.
Expression, Purification and in Silico Characterization of Mycobacterium Smegmatis Alternative Sigma Factor SigB
Authors: Singh Rakesh Kumar , Jaiswal Lav Kumar , Nayak Tanmayee , Rawat Ravindra Singh , Kumar Sanjit , Gupta Ankush
Published: September 2021

Sigma factor B (SigB), an alternative sigma factor (ASF) is very similar to primary sigma factor SigA (σ70) but dispensable for growth in both Mycobacterium smegmatis (Msmeg) and Mycobacterium tuberculosis (Mtb). It is involved in general stress responses including heat, oxidative, surface, starvation stress and macrophage infections. Despite having an extremely short half-life, SigB tends to operate downstream of at least three stress-responsive Extra Cytoplasmic Function (ECF) sigma factors (SigH, SigE, SigL) and SigF involved in multiple signalling pathways. There is very little information available regarding the regulation of SigB sigma factor and its interacting protein partners. Hence, we cloned the SigB gene into pET28a vector and optimized its expression in three different strains of E. coli, viz; (BL21(DE3), C41(DE3) and CodonPlus(DE3)). We also optimized several other parameters for the expression of recombinant SigB including IPTG concentration, temperature, and time-duration. We achieved the maximum expression of SigB at 25 °C in the soluble fraction of the cell which was purified by affinity chromatography using Ni-NTA and further confirmed by Western blotting. Further, structural characterization demonstrates the instability of SigB in comparison to SigA is carried out using homology modelling and structure function relationship. We have done protein-protein docking of RNA polymerase (RNAP) of Mycobacterium smegmatis (Msmeg) and sigB. This effort provides a platform for pulldown assay, structural and other studies with the recombinant protein to deduce the SigB interacting proteins, which might pave the way to study its signalling networks along with its regulation.
Carbazochrome Carbon Nanotube as Drug Delivery Nanocarrier for Anti-bleeding Drug: Quantum Chemical Study
Authors: Sayiner Hakan. S. , Kandemirli Fatma , Dalgic Serap Senturk , Monajjemi Majid , Mollaamin Fatemeh
Published: September 2021

The interaction between drugs and single-walled carbon nanotubes is proving to be of fundamental interest for drug system of delivery and nano-bio-sensing. In this study, the interaction of pristine CNT with carbazochrome, an anti-hemorrhagic or hemostatic agent was investigated with M06-2X functional and 6-31G* and 6-31G** basis sets. All probable positions of related adsorption for these kind drugs were thought-out to find out which one is energetically suitable. Based on the achieved data, the stronger interactions appeared the oxygen atom of C=O group and nitrogen atom of imine groups. The topology analysis of QTAIM (quantum theory of atoms in a molecule) method was accomplished to understand the properties of interactions between the CNT and Carbazochrome. Frontier molecular orbital energies of all systems, global index including stiffness, softness, chemical Gibbs energies and electrophilicity parameters, as well as some other important physical data such as dipole moment, polarizability, anisotropy polarisibility and hyperpolaribility were calculated, evaluated and then compared together. The essence of the formed bonding model progress along the reaction roots were further validated using electron localization function (ELF) calculations. In addition the total, partial, and overlapping population densities of states were calculated for any further discussion. The highest values of adsorption energies were determined in the range of 18.24) up to (22.12) kcal mol-1 for these kind systems. The acceptable recovery time of 849 s was obtained for the desorption of carbazochrome from the CNT surface under UV-Light. The final results exhibit that carbazochrome can serve as a promising carrier and also as sensitive sensors in any kind of practical application.
The Score Card Approach Method of Evaluation of Public Awareness About E-Waste Hazards in Lagos State
Authors: AJAKAYE PAUL ADENIRAN , Paul Ajakaye Adeniran , Emmanuel Somoye , Lawal Owolabi
Published: September 2021

This study was carried out to evaluate the level of awareness of Lagos State residents about e-waste health hazards. Data were collected through the distribution of 424 well-structured and Likert scaled questionnaire with respondents selected based on the proportionate sampling. Unlike the common categorisation of awareness level as either Low or High based on the independent variables like age, sex, educational qualifications; and dependent variables like regulations, mode of disposal of e-wastes, information sources etc, this study adopted the scorecard approach to determine the awareness level in its totality and specific term as either Very Low - 1 or Low - 2 or Moderate - 3 or High - 4 or Very High - 5 in order of categorisation. On the final analysis, the result revealed a score of '2' which implies that the level of awareness is Low. Significance tests were also carried out to examine if any significant differences exist among the respondents based on their gender, age and educational level with respect to the hazardous elements contain in e-waste. The study revealed that statistically, no significant difference exists between the awareness levels of male and female regarding e-waste hazards; no statistically significant difference exists between the awareness levels of respondents about e-waste hazards based on their educational qualifications but there was a statistically significant difference between respondents' ages regarding e-waste hazards.
Molecular imprint of epithelial origin identifies immuno-subtype of thymic epithelial tumors
Authors: Xin Zhongwei , Lin Mingjie , Hao Zhixing , Chen Di , Chen Yongyuan , Chen Xiaoke , Xu Xia , Li Jinfan , Wu Dang , Chai Ying , Wu Pin
Published: September 2021

Thymic epithelial tumors (TETs) are common tumors in human anterior mediastinum with limited biological understanding. Through decoding the immune landscape of tumors, we reclassify TETs into three types based on T cell developmental patterns. We uncover the developmental dysfunction and TCR repertoire of tumor-infiltrating T cells by cell atlas. Moreover, we identify the unique subset of tumor cells with distinct epithelial origin in each TETs type. Furthermore, we demonstrate that KRT14/GNB3+ mTECs-like cell accumulation inhibits the T cell positive selection in type 1 TETs, while CCL25+ cTEC-like cell promotes T cell positive selection in type 2. Interestingly, although CHI3L1+ mTEC-like cell in type 3 TETs loses the function of supporting T cell development, it acquires the capacity to induce CD8+TRMs-mediated response. Finally, we propose a new molecular classification of human TETs using GNB3 and CHI3L1 to distinguish the epithelial origin of tumor cells, which is promising in prognostic prediction.
Carbon Storage of Selected Church Forests in Northern Ethiopia: Implication for Climate Change Mitigation
Authors: Mengistu kehali Dereje , Soromessa Teshome , Eshete Abeje
Published: September 2021

BackgroundForests are known to play an important role in regulating the global climate. Therefore, it serves as natural sink of CO2 to mitigate climate change. Churches and monasteries have a long history of planting, protecting and conserving of trees. This study was conducted on selected church forests, with the objectives of estimating of the carbon stock and its variation along the altitudinal gradients. In light of this, primary data collection was done by field inventory and secondary data was collected from different sources. In order to collect vegetation data particularly above ground biomass (AGB), a total of 64 plots each with the size of 20 m x 20 m at an interval of 100 m, were laid along the established transects at 200 m apart. For litter and soil sample collection, five sub-quadrants 1 m x 1 m were established at four corners and center of every quadrant. Composite method was also used for litter and soil sampling. Data analysis of various carbon pools measured in the forests were analyzed on the excel data sheet and R software. ResultResults revealed that the total mean carbon stock density of church forests was 133.14 t/ha with aboveground biomass carbon of 24.73 t/ha and belowground biomass carbon 6.41t/ha, litter biomass carbon of 1.80 t/ha and soil carbon stock 100.19 t/ha.ConclusionThe result of this study showed that altitude has no significant impact on carbon pools. Overall, this study may increase knowledge on the study site and show contributing of church forests for climate change mitigation.
Establishment of a Combined Diagnostic Model of Abdominal Aortic Aneurysm with Random Forest and Artificial Neural Network
Authors: DUAN YIXUAN , Xie Enrui , Liu Chang , Sun Jingjing , Deng Jie
Published: September 2021

Background Abdominal aortic aneurysm (AAA), a disease with high mortality, is limited by the current diagnostic methods in the early screening. This study aimed to construct a diagnostic model for AAA by using a novel machine learning method, i.e., an ensemble of the random forest (RF) algorithm and an artificial neural network (ANN) (RF-ANN), to identify potential AAA-associated genetic biomarkers. Methods Through a search of the Gene Expression Omnibus (GEO) database, two large-sample gene expression datasets (GSE57691 and GSE47472) were identified and downloaded. The differentially expressed genes (DEGs) between the AAA and normal control samples were identified, followed by Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis using the Database for Annotation, Visualization, and Integrated Discovery (DAVID). Then, RF-ANN was used to identify the key genes from the DEGs, and an AAA diagnostic model was established. Finally, the diagnostic performance of the model was assessed using the area under the receiver operating characteristic curve (AUC) with GSE47472 as a test dataset. Results Using GSE57691, we obtained 2486 DEGs, 52 biological process annotations, 17 cellular component annotations, 17 molecular function annotations, and 13 significantly enriched KEGG pathways. Out of these DEGs, we further identified 74 key candidate feature genes by using the RF machine learning algorithm. The weight of each key gene was calculated by the ANN with GSE57691 as a training dataset to construct an AAA diagnostic model. A transcription factor (TF) regulatory network of key genes was constructed. Finally, GSE47472 was used to validate the model. The AUC value was 0.786, indicating that the model had a highly satisfactory diagnostic performance. Conclusion Potential AAA-associated gene biomarkers were identified, and a diagnostic model of AAA was established. This study may provide a valuable reference for early clinical diagnosis and the search for therapeutic targets of AAA.
A Theory-Based Evaluation of the Leadership for Universal Health Coverage Programme: Insights for Multisectoral Leadership Development in Global Health
Authors: Witter Sophie , Brikci Nouria , Scherer David
Published: September 2021

BackgroundLeadership to manage the complex political and technical challenges of moving towards universal health coverage (UHC) is widely recognised as critical but there are few studies which evaluate how to expand capacities in this area. This article aims to fill some of this gap by presenting the methods and findings of an evaluation of the Leadership for UHC (L4UHC) programme in 2019-20.MethodsGiven the complexity of the intervention and environment, we adopted a theory-driven evaluation approach that allowed us to understand the role of the programme, amongst other factors. Data from a range of sources and tools were compared with a programme theory of change, with analysis structured using an evaluation matrix organised according to the OECD-DAC criteria. Data sources included key informant (KI) interviews (89 in total); surveys of the 80 workshop participants; a range of secondary data sources; case studies in two countries; and observation of activities and modules by the evaluator. Results Participants and KI at global and country reported high relevance of the programme and a lack of alternatives aiming at similar goals. In relation to effectiveness, at the individual level, there was an increase in some competences, particularly for those with less experience at the baseline. Less change was observed in commitment to UHC as that started at a relatively high level. Understanding of UHC complexity grew, particularly for those coming from a non-health background. Connections across institutional divides for team members in-country increased, although variably across the countries, but the programme has not as yet had a major impact on national coalitions for UHC. Impacts on health policy and practice outcomes were evident in two out of seven countries. We examined factors favouring success and explanatory factors. We identified positive but no negative unintended effects. ConclusionsWhile noting methodological constraints, the theory-based evaluation approach is found suitable for assessing and learning lessons from complex global programmes. We conclude that L4UHC is an important addition to the global and national health ecosystem, addressing a relevant need with some strong results, and also highlight challenges which can inform other programmes with similar objectives.
Determination of Thyroidal EDCs Activities Using Approved Human Cell-Based Transactivation Assay
Authors: Seo Hyeyeong , Lee Seok-Hee , Byrd Nick , Willett Catherine , Lee Hee-Seok , Park Yooheon
Published: September 2021

Endocrine-disrupting chemicals (EDCs) interfere with physiological function by mimicking or blocking hormones; these chemicals enter the human body through various materials used in food packaging, among other routes. Thyroid hormones (THs) are very important hormones that control various basic physiological functions. In a previous study, we developed a TH agonist transactivation (TA) assay based on the A549 cell line. However, the assay using A549 showed some limitations since it required 4 days to yield results and showed low sensitivity to the natural form of human triiodothyronine (T3). Therefore, in this study, we have developed a more sensitive TH TA assay based on a HeLa cell line to screen potential TH agonists. We evaluated the TH agonist activity of 17 chemicals, 5 of which showed TH agonist activity. In conclusion, in comparison with the previously developed TA assay, the assay using HeLa cells provided greater accuracy, sensitivity, and specificity, yielding more detailed results for TH agonist chemicals in less time.
One Health in The Brazilian Western Amazon: Helminths in Native Fish and The Food Change of The Puruborá People
Authors: Figueiredo Mayra Araguaia Pereira , Montanha Gisele Oliveira , Manrique Wilson Gómez
Published: September 2021

The aim was to approach an analysis of fish parasites in the Manoel Correia and Caio Espínola Rivers, which border the Aldeia Aperoi, and the report of the Puruborá People on the use of fish as animal protein. Twenty-one fish were collected in the dry season and 15 in the rainy season, totaling 36 specimens, which dissipated cestodes, acanthocephala and nematodes encysted in the musculature, preventing their consumption. Six residents of Aldeia Aperoi were interviewed. The circulation of parasites with zoonotic potential was identified in fish native to the Manoel Correia and Caio Espínola rivers, which border the Aldeia Aperoi, in the Western Amazon of Brazil. It was verified the helplessness of the Puruborá people regarding their inquiries about the environmental imbalance, which causes the loss of fish diversity and, consequently, damage to their culture and their costumes.