bluuebunny/crossref_metadata_2025 huggingface dataset:
Biosurfactant-Enhanced Remediation of Oil-Contaminated Groundwater
Authors: Sanchez-Huerta C. , Hong P. -Y , Zhang S. , Alahmari M. M. , Humam A. A.
Published: June 2024

Groundwater contaminated with hydrocarbons poses a serious hazard to the environment. Current oil-contaminated groundwater remediation techniques include physical, chemical, and biological approaches. Chemical surfactants have the potential of high toxicity due to their low biodegradability. Biosurfactants have demonstrated similar performance to that of chemical surfactants, with the added value of low toxicity. The use of surfactants directly over the top layer of crude oil-contaminating groundwater, where environmental conditions are different from that in above ground surfaces, have yet not been explored in depth. Therefore, this study aims to investigate the potential of four different surfactants for their ability to be deployed in conditions mimicking underground aquifer so as to enhance remediation of oil-contaminated groundwater.

Selected surfactants comprised two chemical surfactants, referred to as A and B, and two biosurfactants, referred to as BS and C. Surfactants were evaluated for their ability (i) to reduce the crude oil layer thickness through facilitating oil dispersion, and (ii) the extent of natural biodegradation it can achieve. Experiments were performed in glass flasks containing synthetic groundwater and crude oil supplemented with surfactant added at the three different surfactants: oil ratios (S:O) 1:5, 1:10 and 1:50. Reduction of crude oil layer thickness, water turbidity, and bacterial cell count were continuously monitored for 60 days to observe the temporal variation of biosurfactant activity towards crude oil.

The performance of surfactants A, C and BS in reducing oil layer thickness was influenced by temperature and S:O ratios. Overall, increase in temperature increased the performance of these three surfactants. S:O ratio was optimal at 1:10 for surfactants A and BS, and at 1:5 for surfactant C. Surfactants A and C reduced the oil layer thickness mainly by means of dispersion and less by biodegradation. In contrast, surfactant BS exhibited an increase in bacterial cell growth that is directly correlated to oil thickness reduction, with an almost equal contribution in the crude oil removal by both dispersion and biodegradation.

Considering our findings, it is of high relevance to apply biosurfactants under optimal conditions to enhance the performance of surfactants in crude-oil removal. This study suggests that in order to develop an effective in-situ biosurfactant-based remediation system for oil decontamination of aquatic environments, different parameters should be considered. Such parameters play an important role in treatment feasibility.
Reservoir and Caprock Compositional Assessment Strategy for Hydrogen Storage
Authors: Chiodoni A. , Fontana M. , Bejtka K. , Gho C. I. , Marzano F. , Pozzovivo V. , Scapolo M. , Mantegazzi A. , Coti C. , Verga F. , Pirri C. F.
Published: June 2024

Carbon geological sequestration and underground hydrogen storage share the need to validate the feasibility of using depleted hydrocarbon reservoirs or deep saline aquifers to receive and host new fluids in the rock pores. Furthermore, these fluids must be safely confined by the cap rock. Despite the rising interest in the underground storage of H2 or mixed with CH4, very few experimental works are available in the literature about the assessment of gas/rock geochemical reactive interactions. In this paper, we present a protocol used to asses gas/rock geochemical interactions of reservoir rocks and caprocks before and after exposure to hydrogen at various conditions, through X-ray diffraction (XRD), scanning electron microscopy (FESEM), Energy-dispersive X-ray spectroscopy (EDS) and Raman Spectroscopy. An Italian field has been selected to assess the impact of gas/rock geochemical interactions with hydrogen at various conditions (pure gas, gas mix in a bioreactor). The optimized protocols were applied to the selected Italian field for the assessment of both caprock or reservoir rock and the outcome was: 1) no evidence of rock compositional variation was observed, 2) no significant morphological or compositional evidence of dissolution and precipitation phenomena was observed after the exposure of the rock to hydrogen. This study represents a step forward to verify the feasibility of underground hydrogen storage.
Significantly Reduce Emissions Using Ammonia Enriched Fuel Gas for Gas Turbines
Authors: Téllez-Schmill R. , Owodunni T.
Published: June 2024

The urgent need to address environmental challenges has prompted refiners and petrochemical operators worldwide to find cleaner and more sustainable energy sources, particularly in their gas turbine equipment (GT). Carbon dioxide (CO2), the primary constituent of greenhouse gases, mainly originates from fossil fuel combustion (Ji et al. 2021). In response, many countries have implemented strict legislation, exemplified by the Paris (COP21) and Glasgow (COP26) Climate Agreements to reduce carbon emissions.

Within this dynamic shift toward sustainable energy, gas turbines (GT) stand at the pinnacle of turbomachinery excellence for power generation. In fact, industry leaders tout them as being unparalleled in this field. GTs are set to maintain a pivotal role as energy conversion equipment, characterized by high thermal efficiency, further affirming their importance in the ever-changing realm of energy infrastructure.

Natural gas, compared to liquid fuels, emerges as a key player in the pursuit of sustainable power solutions. It not only cuts CO2 emissions by 20% but also produces lower levels of NOx. As part of global decarbonization efforts, major gas turbine manufacturers such as Mitsubishi, GE, Siemens, and others are modifying their commercial GT models to burn natural gas with either hydrogen or ammonia. This strategic modification significantly decreases CO2 emissions. Depending on the turbine model, most GT manufacturers can achieve a hydrogen content of up to 100 vol% in the fuel gas for very specific models, as advertised on their websites (GE Vernova 2024; Mitsubishi Power 2021; Siemens Energy 2024).
Repurposing an Offshore Oil and Gas Platform for Green Hydrogen Production: A North Sea Case Study
Authors: Wilcox L. B. , Wiranegara N. K. , Martinez-Felipe A. , Hastings A.
Published: June 2024

Over the next decade, 100 oil and gas platforms, 2,100 North Sea wells, and 7,500 km of pipeline on the UK Continental Shelf are forecast for decommissioning with costs estimated to be £59 billion by 2050. 10% of oil and gas expenditure in the UKCS went into decommissioning in 2021, and that figure rose to 14% in 2022 and is set to rise even further to 19% in 2031. The oil and gas industry aims to reduce these costs by repurposing some of the soon-to-be decommissioned assets for renewable energy generation. This paper presents the findings of a feasibility study conducted to identify opportunities and risks associated with repurposing an offshore oil and gas platform in the North Sea for green hydrogen production. Various technical scenarios were investigated for the case study platform and their profitability was determined using economic calculations. In addition, the results of the techno-economic models were compared with standard decommissioning costs for improved decision making and recommendation purposes. The results of the study highlight the importance of considering various factors such as transmission systems, platform repurposing costs, and long-term financial implications when evaluating the techno-economic viability of different scenarios for offshore hydrogen production. Despite the initial investment for repurposing being three times the cost of decommissioning, the profitability forecast over a 20-year period using net present value analysis at a discount rate of 5% revealed that one of the scenarios holds potential economic benefits if the produced green hydrogen is sold at a price of £6.08/kg.
Acta Physiologiae Plantarum Histochemistry and Gene Expression Using Glycerol in the Pathosystem Musa X Mycosphaerella Fijiensis
Authors: Novaes Ana Paula da Silva , Ramos Andresa Priscila de souza , Nascimento Fernanda dos Santos , Rodrigues Andressa dos santos , Junior Luiz Carlos Souza , Santos Rogerio Merces Ferreira , Santos Rodrigo de Souza  Silva , Amorim Edson PErito , Rocha LEandro de Souza , Mendes Tiago Antonio de Oliveira , ferreira claudia Fortes
Published: June 2024

Black Sigatoka (SN) is a disease that causes leaf lesions that impede the photosynthesis process, culminating in fruits of poor quality banana. Hence, environmentally correct measures, which can present sustainable control of the disease in the field, are extremely important. Therefore, the objective of this study was to verify glycerol-mediated resistance responses in banana plants of the Grande Naine cultivar susceptible to BS. The experiment was conducted in randomized blocks with 5 treatments, namely: control, 0, 3, 5 and 8% glycerol and three replicates. The severity of the disease after the first symptoms was assessed every seven days. For gene expression analysis, the signal transduction genes (STRANS) and the recognition and signaling genes (KINLRR) and the reference genes, L2MU and 25S, were used. Histochemistry was performed to detect calosis with the aid of relative dyes of lugol and aniline blue. By means of leaf tissue clearing, it was possible to visualize pathogen structures from 72 HAI. In the analysis of calosis, the production of the compound was identified in the first evaluations in all glycerol treatments. The target resistance genes, STRANS and KINLRR, had higher expression in the treatments with 5-8% glycerol. From the results presented, glycerol appears to be a good resistance inducer for banana plants when used at a dose of 5%, but further studies are needed to verify the best time to apply treatments, inoculation, and doses to be used.
On-Road Vehicle Aerodynamics with the Ring-of-Fire Concept
Authors: Hüttig Steffen , Kühn Malte , Bloem Guus , Gericke Timo , Sciacchitano Andrea , Akkermans Rinie A.D.
Published: June 2024

This paper presents the first full-scale particle image velocimetry(PIV) measurements to analyze the complete flow field of acar under real driving conditions. The Ring of Fire (RoF) measurementconcept, introduced by Terra et al. (Exp Fluids 58:83, 2017https://doi.org/10.1007/s00348-017-2331-0), is adapted to automotive demandsto validate CFD simulations for further improvements of vehicle aerodynamics.The experiment consists of a tunnel setup, where neutrally buoyant helium-filledsoap bubbles are used as flow tracers and are illuminated by two high-speedlasers; four high-speed cameras captured the particles motion in two separateStereo-PIV-configurations with fields of view of 1.3ˆ0.6m2 and 2.8ˆ2.2m2.Data for a Volkswagen up!, while driving on a test track at a constant speed of33.33 m/s was acquired and processed with standard multi-pass PIV algorithms,in order to quantify the flow field and estimate limits of the described measurementprinciple for on-road car aerodynamics. The resulting velocity fieldsare compared with CFD-simulations, showing agreement for the here consideredcases within 9.65 - 6.97%, based on the root-mean-square error betweenthe experimental and the numerical results. Furthermore, drag calculation fromthe obtained velocity fields based on moment conservation is performed andthe percent difference to wind tunnel measurements reaches values below 3.0%.
Factors Associated with Nursing Students’ Academic Burnout.
Authors: Andargeery Shaherah Yousef , Altaweel Elaf Abdulrahman , Alkorbi Fatima Salem , Alyousef Lamia Abdulaziz , Alanazi Bushra Fayez , Idriss Sara Haroon , Alqahtani Sara Salem , Alkhmees Lana Mohammed
Published: June 2024

Introduction: Academic burnout is a prevalent issue affecting students across different disciplines, including nursing students. Academic burnout negatively impacts students' clinical performance, patient satisfaction, and care quality.
Aim: This study aimed at examining the differences in the mean scores of students’ academic burnout on their demographic characteristics, and the relationship between academic burnout, self-efficacy, psychological distress, and quality of learning experience among undergraduate nursing students.
Methodology: A descriptive, correlational, cross-sectional design with a purposive sampling was used to conduct the study. The questionnaire was sent through Microsoft Forms including demographic questions, Maslach-Burnout Inventory- Student Survey, General Self-Efficacy Survey, Kessler Psychological Distress Scale, and Quality of Learning Experience Scale.
Results: The total number of participants was 286 nursing students. The results depicted that the mean scores of the academic burnout were statistically significant different between students based on their level of English proficiency, program, GPA, having interest in the field of nursing, and support from friends. Nursing students reported moderate levels of self-efficacy, academic burnout, and quality of learning experience. However, the participants are more likely to have severe psychological distress. Academic burnout negatively correlates with self-efficacy, psychological distress, and the quality of learning experience. However, overall quality of learning experience has the weakest correlation, while psychological distress is the strongest.
Conclusion: Our results suggest that academic institutions should ensure that the academic workload and expectations are realistic and aligned with the students' capabilities and avoid overwhelming them with excessive coursework or unrealistic deadlines. Time management skills, coping strategies, problem-solving, goal setting and prioritization should be incorporated in the programs to help students develop a balanced approach to their academic responsibilities.
Revealing the Effect of Different Nitrogen Fertilizer Levels on Rice Yield through 2 Metabolite Evaluation
Authors: zhang yanhong , Sun Tong , Zhu Jinyan , Xiong Qiangqiang , Hu Jinlong , Zhang Haipeng , Zhang Hongcheng , Zhou Nianbing
Published: June 2024

We investigated the differences in metabolites related to rice yield under different nitrogen fertilizer levels and the regulatory roles of key metabolites in metabolic pathways. This study focused on the rice variety Yangchan 15002 and used non-targeted metabolomics methods to detect the metabolic products of rice leaves under three nitrogen fertilizer levels. The yield of Yangchan 15002 plants under high nitrogen (A3: 315 kg hm−2) conditions was significantly higher than that of plants under medium (A2: 270 kg hm−1) and low nitrogen (A1: 180 kg hm−2) conditions. The number of grains per spike in A3 was 6.53% and 18.03% higher than in A2 and A1, respectively. The seed setting rate and thousand-grain weight of plants in the A2 treatment were not significantly different from plants in the A3 treatment. Still, both were significantly higher than A1. The leaf area index and chlorophyll content of plants in A3 were significantly higher than those in A2 and A1. Thirty metabolites related to yield components were identified, among which 4-methylcellulose L-glutamic acid was negatively correlated with C5-branched dicarboxylic acid metabolism and grain number per spike. Triglycerides, L-piperidine, and (S) -2-acetone-2-hydroxybutyric acid were negatively correlated with the number of grains per spike. The increasing application of nitrogen fertilizer improved yield by improving the ear structure of the plants. Specific metabolites in rice leaves are related to the metabolic pathways of amino acid metabolism, carbohydrate metabolism, cofactors, and vitamins under different nitrogen fertilizer conditions. The metabolism of C5-branched dicarboxylic acids in carbohydrate metabolism was significantly positively correlated with the number of grains per spike. These key metabolites are regulated by nitrogen fertilizer and play an important regulatory role in improving the yield and antiaging ability of Yangchan 15002, especially in increasing the number of grains per spike.
A comprehensive spatial assessment of forest fire risk in Huichuan District, China
Authors: Yang Rong , Wang Yi , Liang Fen , Zhang Zhiyuan
Published: June 2024

Background: This study aimed to characterize spatial risks of forest fires in Huichuan District, Zunyi City, Guizhou Province, China. The National Forest and Grassland Fire Risk Census Secondary Platform provided 16 indicators of forest fire risk. Estimates of forest fire risk were made using surveys of wild combustible material, data sharing, mathematical statistics, and literature analysis.
Results: The following results were obtained: (1) Of the 21,210 small classes of forest fire identified for Huichuan District, 9,263 (43.67%), 11,941 (56.3%), and 6 were high, medium-high, and medium low risk, respectively. (2) Of the 1,988 standardized grids: 68, 1,523, 208, 186, and 3 showed high, medium-high, medium-low, low, and no risks, respectively; 64.18% showed medium-high to high risks. (3) Township-level risk assessment divided towns into three risk categories: low, medium-low, and medium-high, to which were assigned three, two, and nine township-level assessment units, representing 0.91%, 5.49%, and 93.67% of the total area, respectively. Among the township evaluation units, two, nine, and three showed medium-low, medium-high risk, and low risks, respectively.
Conclusions: Gaoqiao Street, Donggongsi Street, and Dalian Road have medium-low risk grades; the other nine township evaluation units have medium-high risk categories. Ximalu Street, Shanghai Road, and Gaoqiao Street have low-risk grades. Thus, in order to achieve scientific and efficient fire prevention, the handling of combustible materials, the modification of the species composition of trees, and the enhancement of monitoring and warning sites can be reinforced.
Leveraging Statistical and Machine Learning Techniques to Uncover Determinants of English Performance in Chinese Middle School Students
Authors: Xia Yuzhu
Published: June 2024

This study delves into the predictors of English proficiency among middle school students in China, utilizing the rich dataset provided by the China Education Panel Survey (CEPS). By integrating multilevel modeling and Support Vector Regression (SVR), this research scrutinizes a broad spectrum of factors at the individual, family, class, and school levels. Key predictors identified include students' native language proficiency (Chinese), cognitive aptitude, perceptions of English difficulty, attitudes toward English teachers, and parental involvement. The findings emphasize the significant impact of individual and family-level variables on English proficiency, highlighting the critical role of these modifiable factors. The comparative analysis demonstrates that while both multilevel models and SVR offer valuable insights, their combined application yields a more comprehensive understanding of the predictors and their interactions. This dual-method approach showcases the potential of integrating advanced statistical techniques with machine learning to enhance educational research, thereby informing policy and practice. The study’s insights are vital for developing targeted educational strategies and policies to support bilingual learners in China, ultimately improving language proficiency and educational outcomes.
‘Effect of Anti-oxidant Application on Bleaching Efficacy, Post-Operative Tooth Sensitivity and Oxidative Stress in Smokers and Non-Smokers - A Split-Mouth Triple Blinded Randomized Controlled Trial’
Authors: NAGPAL RITESH , TANEJA SONALI , BHALLA VIDHI KIRAN , JAIN ANSHI
Published: June 2024

Objective
Discoloration impacts dental aesthetics, prompting the need for effective treatment options. Dental bleaching, a conservative approach, utilizes hydrogen peroxide to lighten teeth, yet it can induce tooth sensitivity and oxidative stress. To address these concerns, antioxidants like grape seed extract (GSE) have been proposed. However, their efficacy post-bleaching remains unclear, particularly among smokers facing heightened oxidative stress from nicotine-induced discoloration. This triple-blind randomized controlled trial aimed to investigate the impact of GSE antioxidant on tooth sensitivity and oxidative stress reduction following in-office bleaching, particularly among smokers and non-smokers in the Indian population
Materials and Methods
A prospective, single-center, split-mouth, triple-blind randomized controlled clinical trial was conducted after ethical approval with Thirty smokers and thirty non-smokers having six maxillary anterior teeth with a shade C2 or darker. In-office vital bleaching was done with 35% hydrogen peroxide in two sessions with a seven days interval between each session. Postoperative sensitivity was evaluated with VAS scale, shade evaluation was done using subjective and objective methods and change in the level of oxidative stress biomarker was evaluated using ELISA.
Results
Smokers exhibited higher postoperative tooth sensitivity compared to non-smokers, with significant reduction upon GSE application. Bleaching efficacy, measured by shade guide units and ΔE values, was greater in non-smokers. However, GSE had no significant impact on bleaching outcomes. Biomarker analysis revealed higher oxidative stress levels in smokers, significantly reduced post-bleaching with GSE.
Conclusion
This study highlights challenges smokers face in achieving optimal bleaching outcomes due to heightened oxidative stress. While GSE showed promise in reducing post-bleaching sensitivity and oxidative stress levels in smokers, further research is needed for validation. Nevertheless, GSE application presents a potential avenue for enhancing bleaching outcomes, particularly in smokers, warranting continued investigation.
Clinical Relevance:
By providing insights into the efficacy of GSE in improving bleaching outcomes, this study informs clinical practice, guiding dental professionals in optimizing treatment protocols and managing patient expectations, especially in populations with unique challenges such as smokers. Ultimately, the clinical relevance of this research lies in its potential to improve patient satisfaction and quality of care in the realm of dental bleaching.
Sensitivity of the Planetary Boundary Layer and Cloud Microphysics schemes to the drivers of dispersion and transportation of aerosols
Authors: Rengaraju Sathiyaseelan , Tiwari Pushp Raj , Ghita Adrian , Tatarov Boyan , Das Sushant , Kumar S.
Published: June 2024

The Planetary Boundary Layer (PBL) is the lowest layer of the atmosphere that interacts with the Earth’s surface, and all major meteorology happens within this layer. This paper investigates the simulation of PBL Height (PBLH) and its sensitivity to meteorological parameters as a driver of aerosol dispersion and transport. Four simulations at 6 Km resolution using the Weather Research and Forecasting (WRF) model are run with two PBL schemes (ACM2 and YSU) combined with two Microphysics schemes (LIN and Morrison) for the year 2015 over the European domain. The simulated PBLH and other meteorological parameters that drive the PBL genesis, like temperature and wind speed, are analysed seasonally. In addition to the domain, a few locations from European Aerosol Lidar Network (EARLINET) representing various topography across the domain are chosen for analysis. The model performance in simulating the PBLH, temperature, and wind are examined using various statistical metrics involved in the Taylor diagram and Standard Deviation Error (STDE) methods. The study illustrates the comparisons of model performances for each variable over the domain and at selected station locations near the surface as well as the interfacial layer. We analyze how high (often overestimated) wind speeds affect the development of the Planetary Boundary Layer (PBL), particularly in complex terrains, on a seasonal scale. Our findings attribute unbalanced wind dynamics as a significant factor in this process. The STDE of microphysics schemes combination with YSU scheme shows a relatively 8-20% lesser error than other combinations across the seasons. Despite encountering notable errors over complex terrains, the YSU PBL scheme has performed better due to its ability to handle a wide range of atmospheric conditions.
Response of wheat yield, crop water requirements, and productivity to climate change (Historical simulation and future projection)
Authors: Kashif Muhammad , Ahmad Ijaz , Zaman Muhammad , Akbar Muhammad , Chauhdary Junaid Nawaz
Published: June 2024

Climate change is one of the most vulnerable factors affecting the global agriculture system and it is important to investigate the crop responses to climate change for sustainable development. The present study aimed to investigate the wheat yield responses in line with the crop water requirements (CWR) and crop water productivity (CWP) to climate change in central Punjab, Pakistan. The decision support system for the Agro-technology transfer (DSSAT) model was coupled with climatic change scenarios A2 and B2 of Hadley Centre Coupled Model version 3 (HadCM3) after downscaling to project the crop water productivity, yield, and crop water requirements. Future climate projections indicate that the maximum temperature could increase to 3.9°C − 4.2°C, and the minimum temperature could increase to 1.8°C-2.0°C under the A2 and B2 scenarios till 2080, respectively. Average annual precipitation could increase by 4 to 10% under the A2 scenarios for the 21st century whilst under B2 scenario it increase at start of century (i.e.10.77%) and then reduce in the mid (i.e.3.37%) and end (i.e.4.14%) of the 21st century. Average seasonal crop water requirements will increase by 38 mm and 30 mm under A2 and B2 scenarios by the 2080s. Average wheat yield will decrease by 6.94% / 6.43%, 10.40% / 8.71%, and 9.45% /8.61% under the A2/B2 scenario during the 2020s, 2050s, and 2080s, respectively. Decreasing wheat yield combined with a water deficit would decrease the future crop water productivity (CWP) up to 17.76% and 14.95% under A2 and B2 scenarios, respectively.
Diagnostic efficacy of iron metabolism-related indicators for depression in patients undergoing peritoneal dialysis
Authors: Liu Chenling , Zhu Jingyi , Wang Yunfei , Wei Zhifeng , Cheng Jinxiu , Jin Xin , Liu Shengjun
Published: June 2024

We aimed to analyse the correlation between depression and iron metabolism-related indicators and determine the efficacy of iron metabolism-related indicators in diagnosing depression in patients undergoing peritoneal dialysis (PD). This cross-sectional study included patients undergoing regular follow-up for PD between September 2022 and March 2023. Patient demographics and iron metabolism-related indicators, including serum iron (SI) and ferritin levels and transferrin saturation (TSAT), were collected and analysed. The depression status was assessed using the Patient Health Questionnaire-9. The correlation between iron metabolism-related indicators and concomitant depression was assessed using Spearman’s correlation coefficient. Binary logistic regression analysis was performed to identify independent concomitant depression risk factors. The relevant risk factors’ diagnostic efficacies were assessed using receiver operating characteristic (ROC) curve analysis. Of the 223 patients (121 [54.3%] males and 102 [45.7%] females), 88 (39.5%) had concomitant depression. SI levels (correlation coefficient [r]=-0.741, p < 0.05) and TSATs (r=-0.637, p < 0.05) were significantly correlated with depression and were identified as independent risk factors (odds ratio, 95% confidence interval [CI]: SI 0.434; 0.343–0.549; TSAT 0.782; 0.731–0.837). The ROC curve analysis revealed that SI levels and TSATs were good depression predictors (area under the curve, 95% CI: SI 0.938, 0.905–0.971; TSAT 0.876, 0.831–0.921). SI levels and TSATs were independent risk factors with high diagnostic efficacy for concomitant depression in patients undergoing PD. Thus, these patients’ psychological well-being should be simultaneously monitored.
Octahedral Co2+-O-Co3+ in mixed cobalt spinel promotes active and stable acidic oxygen evolution
Authors: Zhou Daojin , Yu Jiaqi , Tang Jialun , Li Xiao-Yan , Ou Pengfei
Published: June 2024

Cobalt (Co)-based oxides show promising activity as precious metal-free catalysts for the oxygen evolution reaction in proton exchange membrane water electrolysis, but the dissolution of Co has limited the durability of Co3O4 at industrially relevant current densities. This work demonstrates that cation in an octahedral coordination environment accounts for the oxygen evolution activity. Using a mixed inverse-normal phase spinel CoxGa(3-x)O4 as a proof-of-concept example, the designed Co2+-O-Co3+ motifs in octahedral sites trigger oxygen evolution through a kinetically favorable radical coupling pathway. Furthermore, lattice oxygen exchange, a leading factor in catalyst structural degradation for normal Co3O4, is suppressed, as evidenced by isotopic labeling experiments and theoretical calculations. With the optimized catalyst, Co1.8Ga1.2O4, we report an overpotential of 310 mV at 10 mA/cm2, stable operation at 200 mA/cm2 for 200 hours in a three-electrode setup, and a proton exchange membrane electrolyzer operating at 200 mA/cm2 for 450 hours.
Cell Model Representatives of Pediatric Neuroblastoma: Evidence from Transcriptomic Ranking and Pharmacogenomic Connectivity Analysis
Authors: Venkatraman Simran , Pongchaikul Pisut , Balasubramanian Brinda , Vivitthanaporn Pornpun , Soodvilai Sunhapas , Anurathapan Usanarat , Meller Jarek , Hongeng Suradej , Tohtong Rutaiwan , Chutipongtanate Somchai
Published: June 2024

Background
Neuroblastoma is the most common extracranial solid tumor among pediatric patients, with MYCN amplification marking a significant increase in mortality risk. The utilization of neuroblastoma cell lines serves as the first-line model for studying the phenotypic outcomes of novel therapeutic interventions. Selecting cell lines that closely mimic the molecular characteristics of neuroblastomas derived from patients is crucial for enhancing the efficacy of drug discovery. We hypothesized that the similarity of transcriptomic profiles between patient-derived neuroblastoma tumors and neuroblastoma cell lines would enable the identification of cell model representatives (CMRs) that accurately reflect the molecular features of these patient tissues, particularly focusing on MYCN amplification status.
Methods
To test this hypothesis, we conducted a rank-based correlation analysis comparing the transcriptomic profiles of 643 patient-derived tumor tissues (493 from the SEQC/MAQC-III cohort and 150 from the Target cohort) with those of 39 neuroblastoma cell lines (sourced from GSE89413). Pharmacogenomic connectivity analysis was performed using the differentially expressed gene signatures (MYCN-amp vs. MYCN-NA) derived from the CMRs and patient-derived tumor tissues to predict candidate drugs that reverse MYCN-driven oncogenic signals. Finally, a Drug-gene network was performed to narrow down the list of drug candidates that potentially target MYCN interactome.
Results
Our analysis identified COG-N-557, SMS-KAN, and NB-SD as the top three CMRs for MYCN-amplified neuroblastoma, and COG-N-549, FELIX, and SK-N-SH emerged as the top CMRs for MYCN-non-amplified neuroblastoma. Further, pharmacogenomic connectivity map and drug-gene network analyses suggested different drug classes targeting the first- and second-level interactors of MYCN, i.e., kinase inhibitors, topoisomerase inhibitors, and chemotherapeutic agents, might serve as potential therapeutic candidates for MYCN-amplified neuroblastoma. In contrast, all predicted candidates from the poor representative cell lines showed no connection with MYCN interactome.
Conclusion
This bioinformatic study proposes a set of CMRs of patient-derived neuroblastoma tissues, offering a valuable resource for future research aimed at the discovery and validation of novel treatments for pediatric neuroblastoma. Our findings also underscore the potential of targeting the undruggable MYCN through its interactome.
Synthesis, characterisation, and effective photocatalytic degradation applications in organic dye molecules using CdZnS-loaded UIO-66 composites
Authors: Jiang Tao , Zhang Guanyu , Hong Liu , Wu Yun
Published: June 2024

One of the primary sources of industrial wastewater is dye wastewater, which is challenging for conventional water treatment methods to properly degrade because of its complex composition, high chromaticity, difficulty being biochemically destroyed, etc. The utilization of photocatalysts in conjunction with light energy, or photocatalytic technology, is thought to be a sustainable approach to treating dye wastewater due to its many benefits, including high degradation efficiency, rapid reaction times, and the absence of secondary contamination. We chose to employ CdZnS as a carrier in this research, together with composite UIO-66. The degradation of the dye methylene blue was carried out using the composite CdZnS@UIO-66 as a photocatalyst, and the results were compared to those of pure CdZnS and pure UIO-66. The findings demonstrated that CdZnS@UIO-66 had a noticeably greater photocatalytic efficiency than the other two. Up to 99.87% of the methylene blue in 50 mL of aqueous solution was degraded in the experimental reaction with a catalyst dosage of 0.03 g, pH of 7, and an initial concentration of 30 mg/L of methylene blue aqueous solution when exposed to visible light for 90 minutes. This indicates excellent photocatalytic efficacy in the visible range, the formation of an interfacial electron transfer phenomenon within the heterojunction, and the use of UIO-66 as an electron acceptor to further enhanced photocatalytic effect is caused by the development of interfacial electron transfer phenomena within the heterojunction and UIO-66 as an electron acceptor, which further promotes the internal photogenerated electron-hole separation.
Prognostic Value of Quantitative Indexes in Glioblastoma Subregions
Authors: Lijuan Gao , Tao Yuan , Xiaoyun Yang , Yiming Li , Guanmin Quan
Published: June 2024

Background This study developed a nomogram using quantitative indices of this subregion before chemoradiotherapy (CRT) to predict early GBM recurrence. Methods Adult patients with GBM diagnosed between October 2018 and October 2022 were retrospectively analyzed and randomly divided into training and validation groups. Using T1-weighted imaging enhancement and FLAIR fusion maps, the CRT extra-residual FLAIR high-signal area was segmented into categories and the signal intensity of each subzone was measured.The study compared clinical, pathological, and imaging indexes between recurrent and non-recurrent groups, identified independent prognostic risk factors, and developed a prediction model using univariate Cox analysis and LASSO Cox regression analysis. The discriminatory ability of the model was assessed using the C-index, and its performance was evaluated through calibration curves and decision curves. Results A study found that 53.4% of 129 patients with GBM experienced postoperative recurrence. Factors such as the subventricular zone involvement, enhanced regional outside the residual cavity (ER) median, enhanced + unenhanced regional outside the residual cavity (ER + UR) rFLAIR, and corpus callosum involvement were identified as independent predictors of recurrence. The model had a C-index of 0.733 in the training group and 0.746 in the validation group for predicting recurrence at 1 year post-surgery. Patients were also stratified based on these factors.Patients were divided into high and low-risk groups based on their nomogram score, showing a significant difference in progression-free survival between the two groups. Conclusions Quantitative assessment of FLAIR high signal areas in GBM after segmenting subregions shows promise for predicting survival prognosis. Emphasizing specific subregions may improve predictive accuracy.
Construction of a radiogenomic signature based on endoplasmic reticulum stress for predicting prognosis and systemic combination therapy response in hepatocellular carcinoma
Authors: Wu Huai-Yu , Cao Shu-Ya , Xu Zheng-Gang , Wang Tian , Ji Gu-Wei , Wang Ke
Published: June 2024

Background:Hepatocellular carcinomais one of the most common tumors worldwide. Various factors in the tumor microenvironment can lead to the activation of endoplasmic reticulum stress, thereby affecting the occurrence and development of tumors.The objective of our study was to develop and validate a radiogenomic signature based on endoplasmic reticulum stress to predict prognosis and systemic combination therapy response
Methods:Using data from TCGA as a training cohort and data from ICGC as a testing cohort. Univariate Cox regression and multivariate Cox regression analysis were used to identify prognostic-related genes and construct a model. Hepatocellular carcinoma single-cell data obtained from GEO were used to map gene signatures and explore inter-cellular signaling communications. Finally, a radiogenomic signature was used to predict the objective response rate and overall survival.
Results:A total of four gene signatures related to ERS (including STC2, MAGEA3, BRSK2, DDX11) were identified. Macrophages were significantly different between high-risk and low-risk groups. The high-risk group showed higher PD-1 and mutated TP53 scores. Drug sensitivity analysis found that most sensitive drugs target the PI3K/mTOR signaling pathway. Further research revealed the expression of STC2 in the endothelial cells, particularly PLVAP+ endothelial cells, and may regulate the reprogramming and function of macrophages. Furthermore, we identified nine radiomic features and established a radiogenomic signature based on ERS that can predict prognosis and response to systemic combination therapy. This signature can guide systemic combination therapy for patients with unresectable hepatocellular carcinoma.
Conclusions:We established an ERS prognostic model that can predict patient prognosis. We also found that ERS is closely related to the tumor microenvironment and is mainly manifested in the interaction between tumor-associated endothelial cells and tumor-associated macrophages. Moreover, we constructed a radiogenomic signature based on the ERS. This signature can guide subsequent combination therapy for patients with unresectable HCC.
Prostaglandin I2 signaling prevents angiotensin II-induced atrial remodeling and vulnerability to atrial fibrillation in mice
Authors: Zhang Yue , Yuan Meng , Cai Wenbin , Sun Weiyan , Shi Xuelian , Liu Daiqi , Song Wenhua , Yan Yingqun , Chen Tienan , Bao Qiankun , Zhang Bangying , Liu Tong , Zhu Yi , Zhang Xu , Li Guangping
Published: June 2024

Atrial fibrillation (AF) is the most common arrhythmia, and atrial fibrosis is a pathological hallmark of structural remodeling in AF. Prostaglandin I2 (PGI2) can prevent the process of fibrosis in various tissues via cell surface Prostaglandin I2 receptor (IP). However, the role of PGI2 in AF and atrial fibrosis remains unclear. The present study aimed to clarify the role of PGI2 in angiotensin II (Ang II)-induced AF and the underlying molecular mechanism. PGI2 content was decreased in both plasma and atrial tissue from patients with AF and mice treated with Ang II. Treatment with the PGI2 analog, iloprost, reduced Ang II-induced AF and atrial fibrosis. Iloprost prevented Ang II-induced atrial fibroblast collagen synthesis and differentiation. RNA-sequencing analysis revealed that iloprost significantly attenuated transcriptome changes in Ang II-treated atrial fibroblasts, especially mitogen-activated protein kinase (MAPK)-regulated genes. We demonstrated that iloprost elevated cAMP levels and then activated protein kinase A, resulting in a suppression of extracellular signal-regulated kinase1/2 and P38 activation, and ultimately inhibiting MAPK-dependent interleukin-6 transcription. In contrast, cardiac fibroblast-specific IP-knockdown mice had increased Ang II-induced AF inducibility and aggravated atrial fibrosis. Together, our study suggests that PGI2/IP system protects against atrial fibrosis and that PGI2 is a therapeutic target for treating AF.
The prospectively registered trial was approved by the Chinese Clinical Trial Registry. The trial registration number is ChiCTR2200056733. Data of registration was 2022/02/12.
Comparative skin ultrastructure and transcriptome analysis of indigenous, improved meat goats, and dairy goats breeds identified key genes and potential molecular mechanisms affecting goatskin quality
Authors: Hou Xiling , Wang Xianwei , Hou Shuang , Dang Jiangyang , Zhang Xinyu , Tang Jianxiang , Shi Yinghua , Ma Sen , Xu Zejun
Published: June 2024

Background
High-quality goatskins are valuable byproducts usually produced by indigenous goat breeds with poorer production performance in Asia and Africa. However, the genetic and molecular mechanisms underpinning goatskin's biomechanical properties (e.g., tensile strength) remain elusive. Mechanistic exploration of these traits could greatly aid the genetic improvement and genetic resource conservation of native breeds in these regions. To fulfill this purpose, we collected skin tissues from three goat breeds: huai goat (HG), a Chinese native variety producing high-quality goatskins; yudong meat goat (YDMG), a crossbreed of HG and Boer goat; Henan dairy goat (HNDG), a dairy goat breed.
Results
Scanning electronic microscopy analysis of skin tissues found that the collagen fiber diameters, collagen fibril diameters, and crimps significantly differed among the three goat breeds; however, collagen fibril diameters are similar in HG and HNDG. A sum of 230, 775, and 86 differentially expressed genes (DEGs) were identified from YDMG versus HNDG, HG versus HNDG, and YDMG versus HG, respectively. Functional enrichment analysis suggested that signaling pathways involved in fatty acid, retinol, steroid metabolisms, and GO items related to the physical properties of the skin (e.g., collagen-containing extracellular matrix) are significantly overrepresented in DEGs identified from meat versus dairy goats. Furthermore, 106 DEGs (e.g., COL1A1, COL1A2, and SPARC) showed specific expression patterns in HG and YDMG versus HNDG. Items about biophysical features of skin (e.g., extracellular matrix organization and ECM proteoglycans) are markedly enriched. Protein-protein interaction analysis suggested that two growth factors (IGF1 and PDGFD) are latent collagen and other ECM protein expression modulators.
Conclusion
Our study provided preliminary ultrastructural and transcriptomic insights into factors and molecular mechanisms potentially governing goatskin quality. Furthermore, a group of genes, hormones, and growth factors involved in the development and structure of goat skin tissues were identified.
Determination of 229 pesticides residue in edible oil samples using conventional QuEChERS method and solid phase microextraction based on monolithic molecularly imprinted polymer fiber and analysis with GC-MS
Authors: kardani Fatemeh , Jelyani Aniseh zarei , Khezeli Tahere , Hashemi Mohammad , Rashedinia Marzieh , Shariati Saeedeh , Mahdavinia Masoud , Noori Seyyed Mohammad Ali
Published: June 2024

The goal of this research is development of solid phase microextraction based on monolithic molecularly imprinted polymer fiber (SPME-MMIPF) method to determine 229 pesticides in edible oil samples using gas chromatography-mass spectrometry (GC-MS) and comparison of it with the common QuEChERS method. In QuEChERS method, acetonitrile used as extraction solvent and magnesium sulfate used as water absorbing agent. For SPME-MMIPF method, an MMIPF was synthesized by polymerization of methacrylic acid in presence of ethylene glycoldimethacrylate and azo (bis)-isobutyronitrile. The optimal conditions for the SPME-MMIPF method are: extraction time 30 min, desorption time with toluene 20 min and string speed of the aqueous sample 600 rpm. Under optimal extraction condition, the figures of merit were obtained for two methods and compared. The linear range of 1-300 µg kg− 1 for SPME-MMIPF and 10–250 µg kg− 1 for QuEChERS was obtained. The detection limit of SPME-MMIPF (0.321–0.335 µg kg− 1) method was better than the QuEChERS (0.9–2.6 µg kg− 1) method. The results showed a quantification limit of 0.8–2.2 µg kg− 1 for SPME-MMIPF and 1.5–5.2 µg kg− 1 for QuEChERS. The recoveries were in the range of 92–102% and 68–127% for SPME-MMIPF and QuEChERS, respectively.
Analyze the spatial-temporal changes and their environmental impacts on tourist spots in the Chittagong hill tract area of Bangladesh
Authors: Alzaber Md , Islam Md.Rahedul
Published: June 2024

Tourism is related to the cost degradation of the environment and affects the social and cultural spectrum. The growth of the tourism and hospitality sector greatly impacts the environment of mountain tourist areas of Bangladesh. For this, it examines the LULC (Land Use Land Cover) change detection in tourist areas and analyzes its environmental impacts. Analyzing the LULC, NDVI (Normalized Difference Vegetation Index), and NDBI (Normalized Difference Built-Up Index) would help to know about the LULCC detection before 20 years of difference between the tourist spots Sajek, Himchari & Nilgiri by Landsat 5, Landsat 8 & Sentinel-2 satellite imagery and analyzing the LST (Land Surface Temperature) and annual rainfall data which discovers to analyze its environmental impact. Data collection, Satellite image pre-processing, Supervised image Classification, Accuracy Assessment, NDVI, NDBI, LST, and annual rainfall data are processed by the Google Earth Engine code editor with individual code and Area Calculation, LULC change detection, map analysis & design are performed by QGIS 3.28 & 2.18. LULC, NDVI, and NDBI show an increase in urban areas and a decrease in the vegetation rapidly another LST significantly increased, and annual rainfall has decreased in the last 20 years (2003–2023) which can cause the worst climatic condition of the tourists spots environmentally hazardous landslide, cyclone, saline water inundation, forest fire are influencing by rapid growth of urbanization.
Multifunctional radiative cooling cellulose fabrics by in situ grown ZnO for Personal Thermal Management
Authors: Ma Ruijie , Xue Tong , Yu Guo , Yin Yunjie
Published: June 2024

Personal thermal management textiles (PTMs) with cooling functions have garnered substantial interest because of their ability to regulate human body temperature and provide comfort through low energy consumption. However, the preparation of cellulose fabrics such as cotton with cooling function remains a challenge due to the often complex process of developing such textiles. A composite functional cellulosic fabric, based on cotton, is presented in this research to address the various inconveniences caused by hot summer weather. Controlled in situ growth of zinc oxide is achieved through hydrothermal synthesis. The ZnO nanorods deposited on the surface of the cotton fabric have excellent UV shielding ability and synergise solar reflection in the UV band, resulting in a UPF value of 300 + for the modified fabric, and this performance still reaches 80.25 after 100 friction cycles.The surface of the modified cotton fabric has a high solar reflectance (83.88%) and a high heat transfer coefficient (98 W·m− 2·K− 1), and a cooling effect of 3.0°C can be achieved in a simulated heating environment compared with that of the original cotton. Due to these excellent properties and simple operation steps, the cool-feeling fabrics made by in situ growth of ZnO nanorods on the surface of cotton fabrics have certain application prospects.