bluuebunny/crossref_metadata_2025_split huggingface dataset:
Efficacy of DAP coated with bacterial strains and their metabolites for soil phosphorus availability and maize growth
Authors: Murad Sadia , Ahmad Maqshoof , Hussain Azhar , Ali Sajjad , Al-Ansari Nadhir , Mattar Mohamed A. 
Published: May 2024

AbstractPhosphorus (P) use efficiency in alkaline/calcareous soils is only 20% due to precipitation of P2O5 with calcium and magnesium. However, coating Diammonium Phosphate (DAP) with phosphorus solubilizing bacteria (PSB) is more appropriate to increase fertilizer use efficiency. Therefore, with the aim to use inorganic fertilizers more effectively present study was conducted to investigate comparative effect of coated DAP with PSB strains Bacillus subtilis ZE15 (MN003400), Bacillus subtilis ZR3 (MN007185), Bacillus megaterium ZE32 (MN003401) and Bacillus megaterium ZR19 (MN007186) and their extracted metabolites with uncoated DAP under axenic conditions. Gene sequencing was done against various sources of phosphorus to analyze genes responsible for phosphatase activity. Alkaline phosphatase (ALP) gene amplicon of 380bp from all tested strains was showed in 1% w/v gel. Release pattern of P was also improved with coated fertilizer. The results showed that coated phosphatic fertilizer enhanced shoot dry weight by 43 and 46% under bacterial and metabolites coating respectively. Shoot and root length up to 44 and 42% with metabolites coated DAP and 41% with bacterial coated DAP. Physiological attributes also showed significant improvement with coated DAP over conventional. The results supported the application of coated DAP as a useful medium to raise crop yield even at lower application rates i.e., 50 and 75% DAP than non-coated 100% DAP application which advocated this coating technique a promising approach for advancing circular economy and sustainable development in modern agriculture.
Exploring toroidal anvil profiles for larger sample volumes above 4 Mbar
Authors: Zurkowski Claire C. , Yang Jing , Miozzi Francesca , Vitale Suzy , O.’Bannon Earl. F. , Jenei Zsolt , Chariton Stella , Prakapenka Vitali , Fei Yingwei 
Published: May 2024

AbstractWith the advent of toroidal and double-stage diamond anvil cells (DACs), pressures between 4 and 10 Mbar can be achieved under static compression, however, the ability to explore diverse sample assemblies is limited on these micron-scale anvils. Adapting the toroidal DAC to support larger sample volumes offers expanded capabilities in physics, chemistry, and planetary science: including, characterizing materials in soft pressure media to multi-megabar pressures, synthesizing novel phases, and probing planetary assemblages at the interior pressures and temperatures of super-Earths and sub-Neptunes. Here we have continued the exploration of larger toroidal DAC profiles by iteratively testing various torus and shoulder depths with central culet diameters in the 30–50 µm range. We present a 30 µm culet profile that reached a maximum pressure of 414(1) GPa based on a Pt scale. The 300 K equations of state fit to our P–V data collected on gold and rhenium are compatible with extrapolated hydrostatic equations of state within 1% up to 4 Mbar. This work validates the performance of these large-culet toroidal anvils to > 4 Mbar and provides a promising foundation to develop toroidal DACs for diverse sample loading and laser heating.
Evaluation method for ecology-agriculture-urban spaces based on deep learning
Authors: Li Anqi , Zhang Zhenkai , Hong Zenglin , Liu Lingyi , Liu Yuanmin 
Published: May 2024

AbstractWith the increasing global population and escalating ecological and farmland degradation, challenges to the environment and livelihoods have become prominent. Coordinating urban development, food security, and ecological conservation is crucial for fostering sustainable development. This study focuses on assessing the "Ecology-Agriculture-Urban" (E-A-U) space in Yulin City, China, as a representative case. Following the framework proposed by Chinese named "environmental capacity and national space development suitability evaluation" (hereinafter referred to as "Double Evaluation"), we developed a Self-Attention Residual Neural Network (SARes-NET) model to assess the E-U-A space. Spatially, the northwest region is dominated by agriculture, while the southeast is characterized by urban and ecological areas, aligning with regional development patterns. Comparative validations with five other models, including Logistic Regression (LR), Naive Bayes (NB), Gradient Boosting Decision Trees (GBDT), Random Forest (RF) and Artificial Neural Network (ANN), reveal that the SARes-NET model exhibits superior simulation performance, highlighting it’s ability to capture intricate non-linear relationships and reduce human errors in data processing. This study establishes deep learning-guided E-A-U spatial evaluation as an innovative approach for national spatial planning, holding broader implications for national-level territorial assessments.
Oral administration of coenzyme Q10 ameliorates memory impairment induced by nicotine-ethanol abstinence through restoration of biochemical changes in male rat hippocampal tissues
Authors: Ahmadi-Soleimani S. Mohammad , Ghasemi Seyedalireza , Rahmani Mohamad Amin , Gharaei Moein , Mohammadi Bezanaj Maryam , Beheshti Farimah 
Published: May 2024

AbstractSubstance abuse among adolescents has become a growing issue throughout the world. The significance of research on this life period is based on the occurrence of neurobiological changes in adolescent brain which makes the individual more susceptible for risk-taking and impulsive behaviors. Alcohol and nicotine are among the most available drugs of abuse in adolescents. Prolonged consumption of nicotine and alcohol leads to drug dependence and withdrawal which induce various dysfunctions such as memory loss. Coenzyme Q10 (CoQ10) is known to improve learning and memory deficits induced by various pathological conditions such as Diabetes mellitus and Alzheimer's disease. In the present study we investigated whether CoQ10 treatment ameliorates memory loss following a nicotine-ethanol abstinence. Morris water maze and novel object recognition tests were done in male Wistar rats undergone nicotine-ethanol abstinence and the effect of CoQ10 was assessed on at behavioral and biochemical levels. Results indicated that nicotine-ethanol abstinence induces memory dysfunction which is associated with increased oxidative and inflammatory response, reduced cholinergic and neurotrophic function plus elevated Amyloid-B levels in hippocampi. CoQ10 treatment prevented memory deficits and biochemical alterations. Interestingly, this ameliorative effect of CoQ10 was found to be dose-dependent in most experiments and almost equipotential to that of bupropion and naloxone co-administration. CoQ10 treatment could effectively improve memory defects induced by nicotine-ethanol consumption through attenuation of oxidative damage, inflammation, amyloid-B level and enhancement of cholinergic and neurotrophic drive. Further studies are required to assess the unknown side effects and high dose tolerability of the drug in human subjects.
Sign language recognition based on dual-path background erasure convolutional neural network
Authors: Zhang Junming , Bu Xiaolong , Wang Yushuai , Dong Hao , Zhang Yu , Wu Haitao 
Published: May 2024

AbstractSign language is an important way to provide expression information to people with hearing and speaking disabilities. Therefore, sign language recognition has always been a very important research topic. However, many sign language recognition systems currently require complex deep models and rely on expensive sensors, which limits the application scenarios of sign language recognition. To address this issue, based on computer vision, this study proposed a lightweight, dual-path background erasing deep convolutional neural network (DPCNN) model for sign language recognition. The DPCNN consists of two paths. One path is used to learn the overall features, while the other path learns the background features. The background features are gradually subtracted from the overall features to obtain an effective representation of hand features. Then, these features are flatten into a one-dimensional layer, and pass through a fully connected layer with an output unit of 128. Finally, use a fully connected layer with an output unit of 24 as the output layer. Based on the ASL Finger Spelling dataset, the total accuracy and Macro-F1 scores of the proposed method is 99.52% and 0.997, respectively. More importantly, the proposed method can be applied to small terminals, thereby improving the application scenarios of sign language recognition. Through experimental comparison, the dual path background erasure network model proposed in this paper has better generalization ability.
Mesoscale eddy-strengthened deep-sea topographic Rossby waves in the southwestern South China Sea
Authors: Wang Wenzhuo , Liu Zhifei , Zhao Yulong , Lin Baozhi , Zhang Xiaodong , Zhang Jingwen , Li Jiaying , Cao Junyuan , Song Hongzhe 
Published: May 2024

AbstractTopographic Rossby waves (TRWs) dominate the low-frequency variability of deep ocean currents and play a crucial role in energy exchange and material mixing. On the continental slope of the southwestern South China Sea, a deep-water mooring was deployed to observe TRWs for a period of ~ 40 days. The TRWs, with a wavelength of 109 km, account for 41.3% of the subinertial variations. A ray-tracing model was applied to investigate the propagation and energy source. The results showed that the TRWs propagated from the northeast of the mooring location and were most likely caused by the mesoscale eddy disturbances off the Vietnam coast. This study provides a new perspective on examining the impact of mesoscale eddies off Vietnam on abyssal currents.
Evaluation of the clinical use of MGMT methylation in extracellular vesicle-based liquid biopsy as a tool for glioblastoma patient management
Authors: Rosas-Alonso Rocío , Colmenarejo-Fernández Julian , Pernía Olga , Burdiel Miranda , Rodríguez-Antolín Carlos , Losantos-García Itsaso , Rubio Tania , Moreno-Velasco Rocío , Esteban-Rodríguez Isabel , Martínez-Marín Virginia , Yubero Paloma , Costa-Fraga Nicolas , Díaz-Lagares Angel , López-López Rafael , Díaz-Martin Eva , García Juan F. , Sánchez Catalina Vivancos , Gandía-González Maria Luisa , Moreno-Bueno Gema , de Castro Javier , de Cáceres Inmaculada Ibánez 
Published: May 2024

AbstractGlioblastoma (GB) is a devastating tumor of the central nervous system characterized by a poor prognosis. One of the best-established predictive biomarker in IDH-wildtype GB is O6-methylguanine-DNA methyltransferase (MGMT) methylation (mMGMT), which is associated with improved treatment response and survival. However, current efforts to monitor GB patients through mMGMT detection have proven unsuccessful. Small extracellular vesicles (sEVs) hold potential as a key element that could revolutionize clinical practice by offering new possibilities for liquid biopsy. This study aimed to determine the utility of sEV-based liquid biopsy as a predictive biomarker and disease monitoring tool in patients with IDH-wildtype GB. Our findings show consistent results with tissue-based analysis, achieving a remarkable sensitivity of 85.7% for detecting mMGMT in liquid biopsy, the highest reported to date. Moreover, we suggested that liquid biopsy assessment of sEV-DNA could be a powerful tool for monitoring disease progression in IDH-wildtype GB patients. This study highlights the critical significance of overcoming molecular underdetection, which can lead to missed treatment opportunities and misdiagnoses, possibly resulting in ineffective therapies. The outcomes of our research significantly contribute to the field of sEV-DNA-based liquid biopsy, providing valuable insights into tumor tissue heterogeneity and establishing it as a promising tool for detecting GB biomarkers. These results have substantial implications for advancing predictive and therapeutic approaches in the context of GB and warrant further exploration and validation in clinical settings.
Island plants with newly discovered reproductive traits have higher capacity for uniparental reproduction, supporting Baker’s law
Authors: Keller Barbara , Alther Barbara , Jiménez Ares , Koutroumpa Konstantina , Mora-Carrera Emiliano , Conti Elena 
Published: May 2024

AbstractUniparental reproduction is advantageous when lack of mates limits outcrossing opportunities in plants. Baker’s law predicts an enrichment of uniparental reproduction in habitats colonized via long-distance dispersal, such as volcanic islands. To test it, we analyzed reproductive traits at multiple hierarchical levels and compared seed-set after selfing and crossing experiments in both island and mainland populations of Limonium lobatum, a widespread species that Baker assumed to be self-incompatible because it had been described as pollen-stigma dimorphic, i.e., characterized by floral morphs differing in pollen-surface morphology and stigma-papillae shape that are typically self-incompatible. We discovered new types and combinations of pollen and stigma traits hitherto unknown in the literature on pollen-stigma dimorphism and a lack of correspondence between such combinations and pollen compatibility. Contrary to previous reports, we conclude that Limonium lobatum comprises both self-compatible and self-incompatible plants characterized by both known and previously undescribed combinations of reproductive traits. Most importantly, plants with novel combinations are overrepresented on islands, selfed seed-set is higher in islands than the mainland, and insular plants with novel pollen-stigma trait-combinations disproportionally contribute to uniparental reproduction on islands. Our results thus support Baker’s law, connecting research on reproductive and island biology.
Research on the influencing factors of Chinese agricultural brand competitiveness based on DEMATEL-ISM
Authors: Tang Huanchen , Liu Xiaodong , Li Meiyu 
Published: May 2024

AbstractAgricultural products are pivotal to the national economy, and a comprehensive analysis of brand competitiveness significantly contributes to the support of agricultural structural adjustment and modernization. Focusing on the Yangtze River Delta region of China, this study develops an evaluation index system encompassing four dimensions: core brand competitiveness, brand management, market competitiveness, and innovation in branding. Utilizing a DEMATEL-ISM model, this research elucidates the intrinsic relationships among factors that influence brand competitiveness, resulting in a four-tier hierarchical model. The analysis delineates key factors at superficial, intermediate, and profound levels that influence brand competitiveness. Notably, regional production bases, along with innovations in brand technology and systems, emerge as profound influencers. Drawing on these findings, the study recommends strategies to enhance production foundations, accurately define development trajectories, spearhead technological innovation to foster collective reform efforts, and advocate for institutional advancements to bolster healthy brand growth.
Study of equivalent circuit of GaN based laser chip and packaged laser
Authors: Wang Junfei , Hu Junhui , Guan Chaowen , Hou Yuqi , Sun Leihao , Fang Songke , Shi Jianyang , Li Ziwei , Zhang Junwen , Chi Nan , Shen Chao 
Published: May 2024

AbstractHigh-speed GaN-based lasers play a pivotal role in visible light communication (VLC) systems; however, the causes of the limited modulation response of our fabricated laser diode (LD) are not fully understood. Accordingly, we constructed an equivalent circuit model for both the LD and its packaging. This model enabled us to analyze the series resistance and parallel capacitance of the LD at different injection currents. Experiments and simulations were performed to investigate the intrinsic responses of the LD. The series resistance and parallel capacitance are responsible for S21 roll-off at low frequencies. Determination of the packaging design parameters on the modulation response of a transistor outline (TO)-can packaged LD was investigated which is important to achieve the impedance match in the future. The value of each discrete component was determined by fitting the scattering parameters of the equivalent circuit model to the packaged LD. Reducing the series resistance and parallel capacitance improved the modulation response. Our study firstly illustrates the design and manufacture of violet-blue-green laser transmitters with a large modulation bandwidth for ultra-high-speed VLC from the point of the impedance influence.
Predicting high-level visual areas in the absence of task fMRI
Authors: Molloy M. Fiona , Saygin Zeynep M. , Osher David E. 
Published: May 2024

AbstractThe ventral visual stream is organized into units, or functional regions of interest (fROIs), specialized for processing high-level visual categories. Task-based fMRI scans (“localizers”) are typically used to identify each individual’s nuanced set of fROIs. The unique landscape of an individual’s functional activation may rely in large part on their specialized connectivity patterns; recent studies corroborate this by showing that connectivity can predict individual differences in neural responses. We focus on the ventral visual stream and ask: how well can an individual’s resting state functional connectivity localize their fROIs for face, body, scene, and object perception? And are the neural processors for any particular visual category better predicted by connectivity than others, suggesting a tighter mechanistic relationship between connectivity and function? We found, among 18 fROIs predicted from connectivity for each subject, all but one were selective for their preferred visual category. Defining an individual’s fROIs based on their connectivity patterns yielded regions that were more selective than regions identified from previous studies or atlases in nearly all cases. Overall, we found that in the absence of a domain-specific localizer task, a 10-min resting state scan can be reliably used for defining these fROIs.
Three-dimensional magnetic resonance imaging-based statistical shape analysis and machine learning-based prediction of patellofemoral instability
Authors: Nagawa Keita , Inoue Kaiji , Hara Yuki , Shimizu Hirokazu , Tsuchihashi Saki , Matsuura Koichiro , Kozawa Eito , Sugita Naoki , Niitsu Mamoru 
Published: May 2024

AbstractThis study performed three-dimensional (3D) magnetic resonance imaging (MRI)-based statistical shape analysis (SSA) by comparing patellofemoral instability (PFI) and normal femur models, and developed a machine learning (ML)-based prediction model. Twenty (19 patients) and 31 MRI scans (30 patients) of femurs with PFI and normal femurs, respectively, were used. Bone and cartilage segmentation of the distal femurs was performed and subsequently converted into 3D reconstructed models. The pointwise distance map showed anterior elevation of the trochlea, particularly at the central floor of the proximal trochlea, in the PFI models compared with the normal models. Principal component analysis examined shape variations in the PFI group, and several principal components exhibited shape variations in the trochlear floor and intercondylar width. Multivariate analysis showed that these shape components were significantly correlated with the PFI/non-PFI distinction after adjusting for age and sex. Our ML-based prediction model for PFI achieved a strong predictive performance with an accuracy of 0.909 ± 0.015, and an area under the curve of 0.939 ± 0.009 when using a support vector machine with a linear kernel. This study demonstrated that 3D MRI-based SSA can realistically visualize statistical results on surface models and may facilitate the understanding of complex shape features.
Potential drug targets for tumors identified through Mendelian randomization analysis
Authors: Song Na , Shi Pingyu , Cui Kai , Zeng Liqun , Wang Ziwei , Di Wenyu , Li Jinsong , Fan Yanwu , Li Zhanjun , Zhang Jinghang , Su Wei , Wang Haijun 
Published: May 2024

AbstractAccording to the latest cancer research data, there are a significant number of new cancer cases and a substantial mortality rate each year. Although a substantial number of clinical patients are treated with existing cancer drugs each year, the efficacy is unsatisfactory. The incidence is still high and the effectiveness of most cancer drugs remains unsatisfactory. Therefore, we evaluated the human proteins for their causal relationship to for cancer risk and therefore also their potential as drug targets. We used summary tumors data from the FinnGen and cis protein quantitative trait loci (cis-pQTL) data from a genome-wide association study, and employed Mendelian randomization (MR) to explore the association between potential drug targets and nine tumors, including breast, colorectal, lung, liver, bladder, prostate, kidney, head and neck, pancreatic caners. Furthermore, we conducted MR analysis on external cohort. Moreover, Bidirectional MR, Steiger filtering, and colocalization were employed to validate the main results. The DrugBank database was used to discover potential drugs of tumors. Under the threshold of False discovery rate (FDR) < 0.05, results showed that S100A16 was protective protein and S100A14 was risk protein for human epidermal growth factor receptor 2-positive (HER-positive) breast cancer, phosphodiesterase 5A (PDE5A) was risk protein for colorectal cancer, and melanoma inhibitory activity (MIA) was protective protein for non-small cell lung carcinoma (NSCLC). And there was no reverse causal association between them. Colocalization analysis showed that S100A14 (PP.H4.abf = 0.920) and S100A16 (PP.H4.abf = 0.932) shared causal variation with HER-positive breast cancer, and PDE5A (PP.H4.abf = 0.857) shared causal variation with colorectal cancer (CRC). The MR results of all pQTL of PDE5A and MIA were consistent with main results. In addition, the MR results of MIA and external outcome cohort were consistent with main results. In this study, genetic predictions indicate that circulating S100 calcium binding protein A14 (S100A14) and S100 calcium binding protein A16 (S100A16) are associated with increase and decrease in the risk of HER-positive breast cancer, respectively. Circulating PDE5A is associated with increased risk of CRC, while circulating MIA is associated with decreased risk of NSCLC. These findings suggest that four proteins may serve as biomarkers for cancer prevention and as potential drug targets that could be expected for approval.