bluuebunny/crossref_metadata_2025_split huggingface dataset:
Optimizing Energy Efficiency and Reducing Carbon Footprint through Integrated Nutrient Management for Sustainable Maize Production
Authors: Arif Mohd. , Pourouchottamane R , Kumar Ravindra , Kumar Arvind , Kumar Rakesh 
Published: November 2024

Abstract

In India, the energy consumption and greenhouse gas (GHG) emissions from food grain production have increased significantly since the Green Revolution, largely driven by higher use of machinery, fossil fuels, chemical fertilizers, and pesticides. This study explores the energy and carbon footprints of maize (Zea mays L.) cultivation under various integrated nutrient management (INM) practices. It evaluates the effects of three organic manures- goat manure, poultry manure, and vermicompost applied at 5 t ha⁻¹ and five fertilizer levels (0, 25, 50, 75, and 100% of the recommended dose). The research was conducted in a split-plot design with three replications during the kharif seasons of 2021 and 2022 at ICAR-Central Institute for Research on Goats, Mathura, Uttar Pradesh, India. The results showed that combining organic manures with different fertilizer doses significantly influenced crop yield, energy consumption, and carbon emissions. The highest total energy output (137149 MJ ha⁻¹) was achieved with 100% RDF combined with vermicompost, while the highest net energy (118496 MJ ha⁻¹) was recorded with 75% RDF combined with vermicompost. The 75% RDF with vermicompost treatment yielded the highest net carbon gain (2455 kg CE ha⁻¹), however, treatments involving 25%, 50%, and 100% RDF with vermicompost, as well as 50%, 75%, and 100% RDF with poultry and goat manure, showed comparable net carbon gain values to the 75% RDF with vermicompost treatment. Overall, combining organic manures with reduced fertilizer levels enhanced sustainability by optimizing energy and reducing carbon footprints.
Integrating Hydro-Geomorphological Adjustments into Flood Mapping for Enhanced Risk Assessment
Authors: Mukherjee Tuhin , Goel Narendra Kumar , Arya Dhyan Singh , Arora Manohar 
Published: November 2024

Abstract

Extreme rainfall and frequent flooding significantly impact hydro-geomorphic processes that shape the Earth's surface. This often induces increased sedimentation flow, which causes muck flow in the floodplains. It leads to changes in soil erosion/ deposition and flood extent. DEM of difference (DoD) and Elevation Deviation Index (EDI) analyses are widely used to study topographic changes in the earth’s surfaces due to soil erosion/deposition. However, vertical inaccuracies in the original DEMs are directly associated with the DoD, leading to errors in analyzing terrain changes. This paper presents a technique that minimizes the error by normalization, which allows a standardized comparison between the DEMs, making it easier to identify patterns and outliers. This is applied to the past 22 years of the data of the River Shilabati in West Bengal, India. The results of the study reveal a strong positive correlation between soil erosion and flood extent. As the region is frequently experiencing submersion by floodwaters with a simultaneous increase in the trend of extreme events, these findings have profound practical implications for flood management strategies.
RUNX1-mediated LINC01094 promotes gastric cancer through dual targeting of CDKN1A by directly binding RBMS2 and HDAC1
Authors: Zhou Xinyi , Chen Guanhua , Hu Li , Xiao Linmei , Zuo Fei , Shao Hongan , Fei Bojian 
Published: November 2024

Abstract

Background
Accumulating studies have focused on long noncoding RNAs (lncRNAs) because of their regulatory effects on multiple cancers. However, the biological functions and molecular mechanisms of lncRNAs in gastric cancer (GC) remain to be elucidated in depth.
Methods
Long intergenic nonprotein coding RNA 1094 (LINC01094), a differentially expressed lncRNA between GC tissues and adjacent normal tissues, was identified. Moreover, gain- and loss-of-function experiments in vitro and in vivo were carried out. To understand the mechanisms underlying the regulatory effects of LINC01094, we performed RNA pull-down assays, RNA immunoprecipitation assays, chromatin immunoprecipitation assays, luciferase reporter assays, etc.
Results
LINC01094 was markedly upregulated in GC tissues and cell lines, and LINC01094 upregulation was positively correlated with GC malignant behaviours in vitro and in vivo. Mechanistically, LINC01094 downregulated the expression of CDKN1A by interacting with RNA binding motif single stranded interacting protein 2 (RBMS2) and histone deacetylase 1 (HDAC1). Additionally, LINC01094 was confirmed to sponge miR-128-3p and participate in the LINC01094-miR-128-3p-RUNX family transcription factor 1 (RUNX1) feedback loop. Finally, Ro 5-3335, a validated RUNX1 inhibitor, was explored for anticancer drug development in GC.
Conclusions
The LINC01094-miR-128-3p-RUNX1 feedback loop downregulates CDKN1A and promotes GC cooperatively with RBMS2 and HDAC1. Moreover, Ro 5-3335 may have promising therapeutic applications in GC. Hence, our study found an oncogenic lncRNA, LINC01094, which could be a promising target for cancer treatment and diagnosis.
Advanced Knee Point Prediction and Health Monitoring Technique for Improved Electric Vehicle Battery Safety
Authors: Mohanty Namrata , Goyal Neeraj Kumar , Naikan V N Achutha 
Published: November 2024

Abstract

The knee point is a critical threshold indicating a significant change in data behaviour, essential for optimizing predictions in electric vehicles (EVs). Predicting accurate knee points EV batteries is crucial for ensuring battery safety by identifying critical conditions and potential hazards. Leveraging machine learning (ML) algorithms, including support vector machine (SVM), AdaBoost, neural networks (NN), and proposed novel hybrid XGBoost-random forest (XG-RF), the research aims to enhance the accuracy of knee point prediction using slope change method from early battery cycles. Assessment involves absolute error metrics like mean absolute error (MAE) to measure the accuracy of knee point model predictions and mean absolute deviations (MAD) for slope change deviations on dynamic state of health (SOH) curve for different battery chemistries (LFP and NMC) at various temperatures (0℃, 25℃, and 35℃). The proposed XG-RF model consistently outperforms with improved accuracy in terms of lower MAE values as 0.15, 0.13 and 0.13 for NMC and 0.11 for LFP respectively for different temperature. The study's anticipated outcomes extend insights into ML model comparison, novel metric validation, and a comprehensive understanding of algorithms impacting knee point prediction, ultimately contributing to improved EV battery safety.
DNA binding, Molecular Docking and Antimicrobial Studies of Co(III) polypyridyl complexes
Authors: Perka Shyam , Vuradi Ravi Kumar , Gopu Srinivas , Nambigari Navaneetha , Sirasani Satyanarayana 
Published: November 2024

Abstract

Three new cobalt(III) polypyridyl complexes [Co(phen)2(TIPB)]3+(1) {TIPB = 5-(1H-imidazo[4,5-f][1, 10]phenanthrolin-2-yl)thiophene-2-yl-2-boronic acid}, (phen = 1,10-Phenanthroline), [Co(bpy)2(TIPB)]3+(2) (bpy = 2,2’bipyridyl), [Co(dmb)2(TIPB)]3+(3) (dmb = 4, 4’-dimethyl 2, 2’-bipyridine) have been synthesized and characterized by spectral studies FTIR, UV-vis, 1H, 13C-NMR, Mass Spectroscopy and Elemental analysis. The binding properties of all three complexes towards calf-thymus DNA (CT-DNA) have been investigated using UV-visible, emission spectroscopy and viscosity measurements, indicating that all the complexes bind to CT-DNA predominantly through intercalation, but with different affinities. The binding strength of these complexes were 1 > 2 > 3. These complexes cleaved the pBR322 DNA into different forms when irradiated under UV light. The binding studies of Co(III) polypyridyl complexes with ds-DNA were carried out by molecular modeling (MM) studies to identify the binding interactions. The molecular mechanics studies were performed on metal complexes to obtain stable 3D conformers. The energy-minimized 3D structures of metal complexes were docked to the double-stranded DNA. The aromatic ligand, TIPB facilitates the binding of the metal complex with DNA through intercalation. The significant interactions of metal complexes - DNA are the prerequisite features for the metal complexes to be considered as DNA intercalator. The molecular docking data are well substantiated by the available experimental data. The binding selectivity and strength of the metal complex with DNA show that the preferred binding mode involves guanine rich site. It reveals that complexes will bind in between base pairs of DNA and gives information about the binding residues and strength. The antimicrobial studies of these complexes give considerable activity with different bacteria like Staphylococcus aureus, and Bacillus subtilis.
Chitosan hydrogel loaded with copper-tin-sulfur nanosheet materials for skin wound healing
Authors: Ren Mingfei , Yao Jingjing , Yang Dicheng , Zhu Jingyao , Dai Kun , Zhong Yujun , Zhu Jun , Tang Liang , Xu Yan , Yu Jiangming 
Published: November 2024

Abstract

Globally, burns are a serious health problem that disrupts the normal functioning of the skin and increases the risk of bacterial infections. Traditional burn dressings often have difficulties to achieve desired therapeutic results. Therefore, there is an urgent need to develop an ideal wound dressing with good antimicrobial properties, biocompatibility and rapid promotion of burn wound healing. Herein, we prepared a chitosan-based hydrogel loaded with copper-tin-sulfur nanosheet materials (CS/GP/Cu3SnS4), and explored its biocompatibility and antibacterial properties in vitro. The results showed that the antibacterial rate of CS/GP/Cu3SnS4 hydrogel can exceed 95% after contacting with Staphylococcus aureus and Escherichia coli for 4h. Meanwhile, the survival rate of L-929 cells was consistent with that of normal medium, revealing considerable antibacterial effect and biocompatibility which could be used for promoting wound repair. Furthermore, in vivo experiment was conducted to test its dressing properties, antibacterial properties, and the efficiency of promoting wound healing. Compared with control group and CS/GP hydrogel group, the wound healing rate was the highest since the 3rd days of treating with CS/GP/Cu3SnS4.While macrophage secretion factor 68 (CD68) decreased significantly and its expression level was lower than that of control group, and the expression level of VEGF increased significantly, with its expression being 1.18-fold, 3.61-fold, and 1.98-fold higher compared with the CS/GP hydrogel group. These results indicate that CS/GP/Cu3SnS4 hydrogel has a potential application as a burn wound dressing.
Unique N-glycosylation signatures in Aβ oligomer- and lipopolysaccharide-activated human iPSC-derived microglia
Authors: Tang Xinyu , Schindler Ryan , Lucente Jacopo , Oloumi Armin , Tena Jennyfer , Harvey Danielle , Lebrilla Carlito , Zivkovic Angela , Jin Lee-Way , Maezawa Izumi 
Published: November 2024

Abstract

Microglia are the immune cells in the central nervous system (CNS) and become pro-inflammatory/activated in Alzheimer’s disease (AD). Cell surface glycosylation plays an important role in immune cells; however, the N-glycosylation and glycosphingolipid (GSL) signatures of activated microglia are poorly understood. Here, we study comprehensive combined transcriptomic and glycomic profiles using human induced pluripotent stem cells-derived microglia (hiMG). Distinct changes in N-glycosylation patterns in amyloid-β oligomer (AβO) and LPS-treated hiMG were observed. In AβO-treated cells, the relative abundance of bisecting N-acetylglucosamine (GlcNAc) N-glycans decreased, corresponding with a downregulation of MGAT3. The sialylation of N-glycans increased in response to AβO, accompanied by an upregulation of genes involved in N-glycan sialylation (ST3GAL4 and 6). Unlike AβO-induced hiMG, LPS-induced hiMG exhibited a decreased abundance of complex-type N-glycans, aligned with downregulation of mannosidase genes (MAN1A1, MAN2A2, and MAN1C1) and upregulation of ER degradation related-mannosidases (EDEM1-3). Fucosylation increased in LPS-induced hiMG, aligned with upregulated fucosyltransferase 4 (FUT4) and downregulated alpha-L-fucosidase 1 (FUCA1) gene expression, while sialofucosylation decreased, aligned with upregulated neuraminidase 4 (NEU4). Inhibition of sialyation and fucosylation in AβO- and LPS-induced hiMG alleviated pro-inflammatory responses. However, the GSL profile did not exhibit significant changes in response to AβO or LPS activation. AβO- and LPS- specific glycosylation changes could contribute to impaired microglia function, highlighting glycosylation pathways as potential therapeutic targets for AD.
Critical Sustainability Transitions: Relaunching local agriculture after decline
Authors: Lopez-Merino Pedro , Zeppini Paolo , Lazaric Nathalie 
Published: November 2024

Abstract

After decades of agricultural modernization that globalized production , distribution and consumption of food, the beginning of the XXI century has witnessed growing demand for locally-sourced food. This paper presents a stylized model of land-use to explore the potential for reterrito-rialization of food systems, inspired by trends observed in different territories. Using a framework based on phase transitions of collective behaviors, our simulations show the existence of two equilibria and a double transition pattern: an initial critical shift leading to the near-total decline of agriculture, mirroring current local situations (decline), followed by a subsequent opposite transition toward a new equilibrium where agriculture regains significance (relaunch). We extend the model by incorporating network effects, which considerably bolster the dynamics of the relaunch equilibrium. Our findings highlight that sustainability transitions involving collective action are not gradual, but exhibit the non-linear patterns of phase transitions in statistical mechanics. Key model parameters are analyzed as policy levers for a ‘reterritorialization’ of agriculture, aiming to enhance the resilience of local food systems.
Advanced Analysis of Spatiotemporal Behaviors of Modal Structures and Couplings for Plasma Tomography
Authors: Yamasaki Kotaro , Fujisawa Akihide , Nagashima Yoshihiko , Moon Chanho , Kosuga Yusuke , Sasaki Makoto , Nishimura Daiki , Kobayashi T-K. , Kawachi Yuichi , Inagaki Shigeru , Kasuya Naohiro , Yamada Takuma 
Published: November 2024

Abstract

Advanced methods, based on the Fourier-Rectangular Function (FRF) series expansion (K. Yamasaki et al., J.Appl. Phys. 126 043304 (2019)), are proposed to analyze plasma images obtained with tomography. The method is applied to images of the entire cross-section of a cylindrical plasma that is dominated by an oscillatory state. The oscillations are characterized by an azimuthal mode of m = 4 (mother mode), whose spatial pattern is modulated by producing child modes (m = 3 and m = 5) through the nonlinear coupling with m = 1 mode (farther mode). The proposed methods identify the spatiotemporal properties of the modes and their nonlinear coupling propagation along the amplitude trajectory of the father mode. Here, we report the newly developed analysis methods for tomography images and their capabilities to uncover underlying processes in the oscillatory state of turbulent plasmas.
Comprehensive map of the regulatory network triggered by MET exon 14 skipping reveals important involvement of the RAS-ERK signaling pathway
Authors: Tulasne David , Truong Marie-José , Pawlak Geoffrey , Meneboo Jean-Pascal , Sebda Shéhérazade , Fernandes Marie , figeac martin , Elati Mohamed 
Published: November 2024

Abstract

The MET exon 14 skipping mutation (named METex14del) described in lung cancer leads to prolonged activation of signaling pathways and aberrant cell responses, but the link between HGF signaling and cell responses remains unclear. A putative lung cancer regulatory network of influential transcription factors was constructed from the transcriptomes of lung cancer cell lines. Transcriptomic data from METex14del-expressing cells, stimulated or not by HGF, were mapped onto this lung cancer reference network and revealed activation of a major regulatory node composed mainly by the highly influential transcription factors ETS1, FOSL1 and SMAD3. HGF activation of METex14del receptor induced the expression and phosphorylation of these three master regulators and the expression of their predicted target genes involved in migration and invasion. All these molecular and biological effects were inhibited by trametinib, a MEK inhibitor, which was potentiated by combination with capmatinib, a MET inhibitor. New mapping with transcriptomic data from trametinib-treated METex14del cells validated the key role of the RAS-ERK pathway signaling in the activation of ETS1, FOSL1 and SMAD3 regulators and the induction of their target genes in HGF-activated METex14del receptor. Thus, we report an original and powerful strategy to uncover key regulators, essentially transcription factors, activated by specific signaling pathways, which can provide a novel therapeutic strategy using a combination of receptor and signaling inhibitors.
Are AI weather models learning atmospheric physics? A sensitivity analysis of cyclone Xynthia
Authors: Baño-Medina Jorge , Sengupta Agniv , Doyle James D. , Reynolds Carolyn A. , Watson-Parris Duncan , Monache Luca Delle 
Published: November 2024

Abstract

Artificial Intelligence (AI) weather models are explored for initial condition sensitivity studies to analyze the physicality of the relationships learned. Gradients (or sensitivities) of the target metric of interest are computed with respect to the variable fields at initial time by means of the backpropagation algorithm and gradient descent, which do not assume linear perturbation growth. Here, sensitivities from an AI model at 36-hour lead time were compared to those produced by an adjoint of a dynamical model for an extreme weather event, cyclone Xynthia, presenting very similar structures and with the evolved perturbations leading to similar impacts. This demonstrates the ability of the AI model to learn physically-meaningful spatio-temporal links between atmospheric processes. These findings should enable researchers to conduct initial condition studies in minutes, potentially at lead times into the non-linear regime (typically > 5 days), with important applications in observing network design and the study of atmospheric dynamics.
Albumin replacement reduces mortality in hypoalbuminemic rats with LPS-induced endotoxemia
Authors: Barbeiro Hermes Vieira , Catanozi Sérgio , Barbeiro Denise Frediani , Lorigados Clara Batista , Passarelli Marisa , Soriano Francisco Garcia 
Published: November 2024

Abstract

Background: Hypoalbuminemia may influence the clinical response and mortality induced by endotoxemia. Sepsis impairs adequate tissue perfusion, and early volume resuscitation by albumin or crystalloid administration is critical for clinical outcomes and survival.
Methods: This study analyzed in hypoalbuminemic rats the effects of endotoxemia on vascular reactivity, cardiac function, oxidative and inflammatory profile, and survival. In addition, mortality was accessed after albumin replacement. Endotoxemia was induced in male Sprague Dawley (SD) or Nagase analbuminemic rats (NAR) using either lipopolysaccharide (LPS) injection or cecal ligation and puncture (CLP), with or without subsequent albumin replacement. Survival rates were assessed every 8 h for 5 days following LPS injection. Hemodynamic evaluations were conducted 4 hours post-LPS injection by measuring mean arterial pressure (MAP), left ventricular end-diastolic pressure, dP/dtmax, and dP/dtmin. Vascular reactivity of aortic rings was recorded 4 hours post-LPS. Oxidative stress, measured by thiobarbituric acid reactive substances (TBARS), and cytokine levels, determined by ELISA, were assessed at 1.5 and 4 hours post-LPS injection. Comparisons among groups were performed using ANOVA with post-hoc Tukey-Kramer analysis
Results: Survival rates were lower in NAR+LPS (25%) and NAR+CLP (10%) compared to SD+LPS (80%) and SD+CLP (40%), but albumin replacement improved survival in NAR+LPS (25%) as compared to NAR+LPS+ALB (55%). Severe hemodynamic impairments, including reduced cardiac function and vascular reactivity, were observed in NAR+LPS. Baseline and post-LPS plasma levels of TBARS and nitric oxide were elevated in NAR, while TNF, IL-6, and IL-10 were higher in SD+LPS compared to NAR+LPS.
Discussion: Subgroup analysis of studies with volume infusion suggests that septic patients with hypoalbuminemia may benefit from albumin infusion during shock. To further investigate the role of prior hypoalbuminemia in septic shock and the underlying pathophysiological mechanisms, we conducted a translational study bridging clinical findings with experimental research. The results demonstrate that hypoalbuminemia cause alterations in endothelial and vascular muscle function as well as cardiac dysfunction.
Conclusion: Hypoalbuminemia in rats increase mortality from endotoxemia, associated with severe cardiovascular dysfunction and oxidative stress. Albumin replacement in hypoalbuminemic rats reduced mortality in endotoxemia-induced sepsis.
A Novel Hybrid Differential Evolutionary Algorithm for Solving Multi-objective Distributed Permutation Flow-shop Scheduling Problem
Authors: Du Xinzhe , Zhou Yanping 
Published: November 2024

Abstract

The Distributed Permutation Flow-shop Scheduling Problem (DPFSP) is a classic issue in distributed scheduling that involves job allocation and processing order within a factory, and it is known to be NP-hard. Numerous researchers have proposed various intelligent optimization algorithms to address the DPFSP; however, achieving solutions of sufficient quality to meet production practice requirements remains challenging. To tackle the multi-objective DPFSP, this paper proposes a novel hybrid differential evolutionary algorithm aimed at minimizing both the maximum completion time and delay time. In this algorithm, Bernoulli chaotic mapping is applied during the population initialization process to enhance the diversity of the initial population. Additionally, an adaptive mutation factor and crossover rate are designed to balance the global and local search capabilities of the algorithm. Furthermore, a novel selection strategy is constructed based on the NEH algorithm, specular reflection learning, and Pareto dominance relation to improve the quality of the solution set when solving instances of varying sizes. This strategy enhances the algorithm's optimization ability and helps it escape local optima. The effectiveness and superiority of the proposed algorithm are verified through 24 instances of different sizes. The results demonstrate that the proposed algorithm outperforms other improved algorithms in terms of convergence, and the uniformity and diversity of the solution set, making it an effective solution for the multi-objective distributed permutation flow-shop scheduling problem.