bluuebunny/crossref_metadata_2025_split huggingface dataset:
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

Abstract

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

Abstract

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

Abstract

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

Abstract

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

Abstract

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

Abstract

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

Abstract

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

Abstract

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

Abstract

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

Abstract

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

Abstract

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.