bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Move Forward: Exploring National Identity Through Non-linear Principal Component Analysis in Germany
Authors: Bruinsma Bastiaan , Mußotter Marlene 
Published: April 2022

AbstractIn research on national identity, scholars have developed a wide variety of approaches to measure and better understand this ubiquitous yet complex concept. To date, most of these approaches have been theory-driven, while only a very few have been data-driven. In this article, we aim to contribute to the latter by introducing a new data-driven method that has not been applied yet—that of non-linear principal component analysis (NLPCA). In contrast to other commonly used methods such as factor analysis, NLPCA distinguishes itself by making relatively few assumptions about the data and by allowing for greater flexibility when discovering underlying dimensions of such a complex concept as national identity. Drawing on the 2013 ISSP National Identity module, our analysis focuses on the case of Germany, also taking into account Western and Eastern Germany. Running an NLPCA, we find four dimensions that cover the multidimensionality of national identity: nationalistic attitudes, national pride and attachment, cosmopolitan beliefs, and membership criteria defining national belonging. This article contributes to the empirical debate on measuring national identity by suggesting a new and flexible methodological approach that better grasps the concept’s complexity and which we believe can move empirical research on national identity forward in and beyond Germany.
Operationalising emission and toxicity modelling of pesticides in LCA: the OLCA-Pest project contribution
Authors: Nemecek Thomas , Antón Assumpció , Basset-Mens Claudine , Gentil-Sergent Céline , Renaud-Gentié Christel , Melero Carlos , Naviaux Pierre , Peña Nancy , Roux Philippe , Fantke Peter 
Published: April 2022

Abstract
Purpose
Current field emission modelling and toxicity characterisation of pesticides suffer from several shortcomings like mismatches between LCI databases and LCIA methods, missing characterisation factors, missing environmental compartments, and environmental impact pathways. The OLCA-Pest project was implemented to address these aspects and to operationalise the assessment of pesticides in LCA. Based on this effort, we propose an approach to integrate pesticide emissions into LCI databases.

Methods
The PestLCI Consensus Model has been developed in order to estimate emission fractions to different environmental compartments. The initial distribution fractions should be linked to the compartments air, agricultural soil, natural soil, and freshwater. Emissions to off-field surfaces are hereby distributed between agricultural soil, natural soil, and freshwater by using surface cover data. Deposition on the crop surface should be recorded in an emission compartment crop with 13 sub-compartments for crop archetypes for both food and non-food uses. Default emission fractions are provided to calculate the emission fractions for different pesticide application scenarios.

Results and discussion
A sensitivity analysis shows the effects of the application technique, drift reduction, crop and development stage, field width, and buffer zone on the initial distribution fractions of field-applied pesticides. Recommendations are given for the implementation of a set of default initial distribution fractions into LCI databases, for the organisation of metadata, and for the modelling of pesticide residues in food along the supply chain (processing, storage). Priorities for further research are: improving the modelling of pesticide secondary emissions, further extending emission modeling (e.g. additional application techniques, including cover crops), considering metal-based pesticides in emission models, and systematically assessing human health impacts associated with pesticide residues in food crops.

Conclusions
The proposed approach allows to preserve the mass balance of the pesticide emitted after application, to make a consistent assessment of ecotoxicity and human toxicity, to define a clear and consistent interface between the LCI and LCIA phases, to estimate initial emission distribution fractions based on existing data, to document metadata transparently and efficiently within crop datasets, and to model the removal of pesticide residues in food during processing.
Burden of treatment, emotion work and parental burnout of mothers to children with or without special needs: A pilot study
Authors: Findling Yifat , Barnoy Sivia , Itzhaki Michal 
Published: April 2022

Abstract
The psychological phenomenon of Parental Burnout (PB) results from an imbalance between continuous exposure to chronic parenting stress and available coping resources. The study’s aim was to examine relationships between mothers’ perceived burden of treatment and PB, and their ability to utilize emotion work (EW) as a psychological coping resource. Ninety-eight Israeli mothers (46 had children with special needs with disabilities—W-SND, and 52 had children without special needs—WO-SN) completed questionnaires assessing their perception of burden of treatment, EW and PB. According to the findings, mothers of children W-SND reported significantly higher PB, a higher perceived burden of treatment and deeper EW than mothers of children WO-SN. Additionally, among all the mothers, a positive significant correlation was found between perceived burden of treatment and PB, while among mothers of children W-SND, positive correlations were found between their perceived burden of treatment and deep EW, and between deep EW and PB. These findings suggest that among mothers of children W-SND, PB is related to their perception of the burden of treatment and to performing deep EW. Additional psychological, cultural and environmental factors should be investigated, in order to gain new perspectives regarding PB as a psychological phenomenon that affects parenting and the ability to utilize coping mechanisms for mothers generally and for mothers of children W-SND especially.
Machine Learning-Based Evaluation of Susceptibility to Geological Hazards in the Hengduan Mountains Region, China
Authors: Zhao Jiaqi , Zhang Qiang , Wang Danzhou , Wu Wenhuan , Yuan Ruyue 
Published: April 2022

AbstractThe Hengduan Mountains Region (HMR) is one of the areas that experience the most frequent geological hazards in China. However, few reports are available that address the geological hazard susceptibility of the region. This study developed six machine learning models to assess the geological hazard susceptibility. The results show that areas with medium and high susceptibility to geological hazards as a whole account for almost 21% of the total area, while both are 18% when it comes to the single hazard of landslide and rockfall respectively. Medium and high geological hazard susceptibility is found in three parts of the HMR with different characteristics: (1) the central and southern parts, where the population of the region concentrates; (2) the northern part, where higher geological hazard susceptibility is found along the mountain ranges; and (3) the junction of Tibet, Yunnan, and Sichuan in the eastern part, which is prone to larger-scale geological hazards. Of all the potential influencing factors, topographic features and climatic variables act as the major driving factors behind geological hazards and elevation, slope, and precipitation are crucial indicators for geological hazard susceptibility assessment. This study developed the geological hazard susceptibility maps of the HMR and provided information for the multi-hazard risk assessment and management of the region.
Vertical take-off and landing hybrid unmanned aerial vehicles: An overview
Authors: Rehan M. , Akram F. , Shahzad A. , Shams T.A. , Ali Q. 
Published: April 2022

AbstractThis article presents the research status and development trends of Vertical Take-off and Landing hybrid Unmanned Aerial Vehicles. In this research, a special emphasis is laid on the design philosophies, analysis techniques, dynamic modeling, and control laws of hybrid VTOL UAVs. It studies and compares various design configurations of hybrid VTOL UAVs, based on key design features such as aerodynamic performance, flight stability, structural strength, propulsive power, avionics systems, flight controls, autonomy, ease of fabrication and flight transition mechanisms. The benefits and shortcomings of each design configuration are expressed in detail. A selection problem is formulated in a fuzzy environment and the Multi-Attribute Decision-Making technique is employed. Ongoing research projects in the field are discussed and a novel design of tail sitter hybrid VTOL UAV is presented by the authors. This work serves as a useful guide for the prospective explorers of this challenging field of research.
Effects of Mixed Layer Depth on Phytoplankton Biomass in a Tropical Marginal Ocean: A Multiple Timescale Analysis
Authors: Hou Li‐Tzu , Wang Bo‐Shian , Lai Chao‐Chen , Chen Tzong‐Yueh , Shih Yung‐Yen , Shiah Fuh‐Kwo , Ko Chia‐Ying 
Published: April 2022

AbstractIn open oceans, changes in mixed layer depth (MLD) may affect phytoplankton growth and biomass variations via the regulation of nutrient supply from deep waters. Estimates of relationships between variability in phytoplankton dynamics and the MLD remain limited, especially at different time scales. We compiled and analyzed averaged euphotic‐depth‐integrated chlorophyll‐a (IChl‐a) and surface chlorophyll‐a (SChl‐a) concentrations collected from 27 cruises during the period of 1999–2019 in the tropical northern South China Sea (SCS). Seasonal differences existed in both averaged IChl‐a and SChl‐a concentrations, with significantly high concentrations in the cold season. Inconsistent relationships between the averaged IChl‐a and SChl‐a concentrations between seasons implied that the use of SChl‐a concentration as a common indicator of phytoplankton biomass dynamics should be performed with caution. Over the past decades in the northern SCS, the averaged IChl‐a, SChl‐a, and MLD decreased to a greater extent in the cold season than in the warm season, while sea surface temperature (SST) rose rapidly and dramatically in both seasons. The MLD was observed to have better correlations with the averaged IChl‐a and SChl‐a concentrations than the SST in the time‐series data. Our results highlight the importance of IChl‐a concentration, which is an overall measure of phytoplankton responses to euphotic zone conditions, and the MLD could be used as a good index for changes in phytoplankton biomass under climate change.
Positive modulation of N-methyl-D-aspartate receptors in the mPFC reduces the spontaneous recovery of fear
Authors: Lee Boyoung , Pothula Santosh , Wu Min , Kang Hyeyeon , Girgenti Matthew J. , Picciotto Marina R. , DiLeone Ralph J. , Taylor Jane R. , Duman Ronald S. 
Published: April 2022

AbstractN-methyl-D-aspartate receptor (NMDAR) modulators have recently received increased attention as potential therapeutics for posttraumatic stress disorder (PTSD). Here, we tested a novel NMDAR-positive modulator, NYX-783, in the following two rodent models of PTSD: an auditory fear-conditioning model and a single-prolonged stress (SPS) model. We examined the ability of NYX-783 to reduce subsequent fear-based behaviors by measuring enhanced fear extinction and reduced spontaneous recovery (spontaneous return of fear) in male mice. NYX-783 administration significantly reduced spontaneous recovery in both PTSD models and enhanced fear extinction in the SPS model. Furthermore, NYX-783 increased the NMDA-induced inward currents of excitatory and inhibitory neurons in the infralimbic medial prefrontal cortex (IL mPFC) and that the GluN2B subunit of NMDARs on pyramidal neurons in the IL mPFC is required for its effect on spontaneous recovery. The downstream expression of brain-derived neurotrophic factor was required for NYX-783 to achieve its behavioral effect. These results elucidate the cellular targets of NYX-783 and the molecular mechanisms underlying the inhibition of spontaneous recovery. These preclinical findings support the hypothesis that NYX-783 may have therapeutic potential for PTSD treatment and may be particularly useful for inhibiting spontaneous recovery.
The promising role of new molecular biomarkers in prostate cancer: from coding and non-coding genes to artificial intelligence approaches
Authors: Alarcón-Zendejas Ana Paula , Scavuzzo Anna , Jiménez-Ríos Miguel A. , Álvarez-Gómez Rosa M. , Montiel-Manríquez Rogelio , Castro-Hernández Clementina , Jiménez-Dávila Miguel A. , Pérez-Montiel Delia , González-Barrios Rodrigo , Jiménez-Trejo Francisco , Arriaga-Canon Cristian , Herrera Luis A. 
Published: April 2022

AbstractBackgroundRisk stratification or progression in prostate cancer is performed with the support of clinical-pathological data such as the sum of the Gleason score and serum levels PSA. For several decades, methods aimed at the early detection of prostate cancer have included the determination of PSA serum levels. The aim of this systematic review is to provide an overview about recent advances in the discovery of new molecular biomarkers through transcriptomics, genomics and artificial intelligence that are expected to improve clinical management of the prostate cancer patient.MethodsAn exhaustive search was conducted by Pubmed, Google Scholar and Connected Papers using keywords relating to the genetics, genomics and artificial intelligence in prostate cancer, it includes “biomarkers”, “non-coding RNAs”, “lncRNAs”, “microRNAs”, “repetitive sequence”, “prognosis”, “prediction”, “whole-genome sequencing”, “RNA-Seq”, “transcriptome”, “machine learning”, and “deep learning”.ResultsNew advances, including the search for changes in novel biomarkers such as mRNAs, microRNAs, lncRNAs, and repetitive sequences, are expected to contribute to an earlier and accurate diagnosis for each patient in the context of precision medicine, thus improving the prognosis and quality of life of patients. We analyze several aspects that are relevant for prostate cancer including its new molecular markers associated with diagnosis, prognosis, and prediction to therapy and how bioinformatic approaches such as machine learning and deep learning can contribute to clinic. Furthermore, we also include current techniques that will allow an earlier diagnosis, such as Spatial Transcriptomics, Exome Sequencing, and Whole-Genome Sequencing.ConclusionTranscriptomic and genomic analysis have contributed to generate knowledge in the field of prostate carcinogenesis, new information about coding and non-coding genes as biomarkers has emerged. Synergies created by the implementation of artificial intelligence to analyze and understand sequencing data have allowed the development of clinical strategies that facilitate decision-making and improve personalized management in prostate cancer.
O-GlcNAcylation and stablization of SIRT7 promote pancreatic cancer progression by blocking the SIRT7-REGγ interaction
Authors: He Xiaoman , Li Yongzhou , Chen Qing , Zheng Lei , Lou Jianyao , Lin Chuanshuai , Gong Jiali , Zhu Yi , Wu Yulian 
Published: April 2022

AbstractPancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers and its dismal prognosis indicates the urgent need to elucidate the potential oncogenic mechanisms. SIRT7 is a classic NAD+-dependent deacetylase that stabilizes the transformed state of cancer cells. However, its functional roles in PDAC are still unclear. Here, we found that SIRT7 expression is upregulated and predicts poor prognosis in PDAC. Then we screened the new interacting proteins of SIRT7 by mass spectrometry and the results showed that SIRT7 can interact with O-GlcNAc transferase (OGT). O-GlcNAcylation stabilizes the SIRT7 protein by inhibiting its interaction with REGγ to prevent degradation, and hyper-O-GlcNAcylation in pancreatic cancer cells leads to hypoacetylation of H3K18 via SIRT7, which promotes transcriptional repression of several tumour suppressor genes. In addition, SIRT7 O-GlcNAcylation at the serine 136 residue (S136) is required to maintain its protein stability and deacetylation ability. In vivo and in vitro experiments showed that blocking SIRT7 O-GlcNAcylation at S136 attenuates tumour progression. Collectively, we demonstrate that O-GlcNAcylation is an important post-translational modification of SIRT7 in pancreatic cancer cells, and elucidating this mechanism of SIRT7 is expected to pave the way for the development of novel therapeutic methods in the future.
Non-coding RNAs and ferroptosis: potential implications for cancer therapy
Authors: Balihodzic Amar , Prinz Felix , Dengler Michael A. , Calin George A. , Jost Philipp J. , Pichler Martin 
Published: April 2022

AbstractFerroptosis is a recently defined form of regulated cell death, which is biochemically and morphologically distinct from traditional forms of programmed cell death such as apoptosis or necrosis. It is driven by iron, reactive oxygen species, and phospholipids that are oxidatively damaged, ultimately resulting in mitochondrial damage and breakdown of membrane integrity. Numerous cellular signaling pathways and molecules are involved in the regulation of ferroptosis, including enzymes that control the cellular redox status. Alterations in the ferroptosis-regulating network can contribute to the development of various diseases, including cancer. Evidence suggests that ferroptosis is commonly suppressed in cancer cells, allowing them to survive and progress. However, cancer cells which are resistant to common chemotherapeutic drugs seem to be highly susceptible to ferroptosis inducers, highlighting the great potential of pharmacologic modulation of ferroptosis for cancer treatment. Non-coding RNAs (ncRNAs) are considered master regulators of various cellular processes, particularly in cancer where they have been implicated in all hallmarks of cancer. Recent work also demonstrated their involvement in the molecular control of ferroptosis. Hence, ncRNA-based therapeutics represent an exciting alternative to modulate ferroptosis for cancer therapy. This review summarizes the ncRNAs implicated in the regulation of ferroptosis in cancer and highlights their underlying molecular mechanisms in the light of potential therapeutic applications.
Construction of emissive ruthenium(II) metallacycle over 1000 nm wavelength for in vivo biomedical applications
Authors: Xu Yuling , Li Chonglu , Lu Shuai , Wang Zhizheng , Liu Shuang , Yu Xiujun , Li Xiaopeng , Sun Yao 
Published: April 2022

AbstractAlthough Ru(II)-based agents are expected to be promising candidates for substituting Pt-drug, their in vivo biomedical applications are still limited by the short excitation/emission wavelengths and unsatisfactory therapeutic efficiency. Herein, we rationally design a Ru(II) metallacycle with excitation at 808 nm and emission over 1000 nm, namely Ru1085, which holds deep optical penetration (up to 6 mm) and enhanced chemo-phototherapy activity. In vitro studies indicate that Ru1085 exhibits prominent cell uptake and desirable anticancer capability against various cancer cell lines, especially for cisplatin-resistant A549 cells. Further studies reveal Ru1085 induces mitochondria-mediated apoptosis along with S and G2/M phase cell cycle arrest. Finally, Ru1085 shows precise NIR-II fluorescence imaging guided and long-term monitored chemo-phototherapy against A549 tumor with minimal side effects. We envision that the design of long-wavelength emissive metallacycle will offer emerging opportunities of metal-based agents for in vivo biomedical applications.
Spontaneous charging affects the motion of sliding drops
Authors: Li Xiaomei , Bista Pravash , Stetten Amy Z. , Bonart Henning , Schür Maximilian T. , Hardt Steffen , Bodziony Francisco , Marschall Holger , Saal Alexander , Deng Xu , Berger Rüdiger , Weber Stefan A. L. , Butt Hans-Jürgen 
Published: April 2022

AbstractWater drops moving on surfaces are not only an everyday phenomenon seen on windows but also form an essential part of many industrial processes. Previous understanding is that drop motion is dictated by viscous dissipation and activated dynamics at the contact line. Here we demonstrate that these two effects cannot fully explain the complex paths of sliding or impacting drops. To accurately determine the forces experienced by moving drops, we imaged their trajectory when sliding down a tilted surface, and applied the relevant equations of motion. We found that drop motion on low-permittivity substrates is substantially influenced by electrostatic forces. Our findings confirm that electrostatics must be taken into consideration for the description of the motion of water, aqueous electrolytes and ethylene glycol on hydrophobic surfaces. Our results are relevant for improving the control of drop motion in many applications, including printing, microfluidics, water management and triboelectric nanogenerators.
Smoking has disruptive effects on the small bowel luminal microbiome
Authors: Leite Gabriela , Barlow Gillian M. , Hosseini Ava , Parodi Gonzalo , Pimentel Maya L. , Wang Jiajing , Fiorentino Alyson , Rezaie Ali , Pimentel Mark , Mathur Ruchi 
Published: April 2022

AbstractTobacco use is the leading preventable cause of cancer, and affects the respiratory, oral, fecal, and duodenal mucosa-associated microbiota. However, the effects of smoking on the duodenal luminal microbiome have not been studied directly. We aimed to compare the duodenal luminal microbiome in never-smokers, current smokers, and ex-smokers who quit ≥ 10 years ago. In a cross-sectional study, current smokers (CS, n = 24) were identified and matched to never-smokers (NS, n = 27) and ex-smokers (XS, n = 27) by age (± 5 years), body mass index (BMI, ± 3 kg/m2), and sex. Current antibiotic users were excluded. The duodenal luminal microbiome was analysed in 1 aspirate sample per subject by 16S rRNA gene sequencing. Relative abundances (RA) of families associated with increased duodenal microbial diversity, Prevotellaceae, Neisseriaceae, and Porphyromonadaceae, were significantly lower in CS vs. NS. This was driven by lower RA of unknown Prevotella and Porphyromonas species, and Neisseria subflava and N. cinerea, in CS. In contrast, RA of Enterobacteriaceae and Lactobacillaceae (associated with decreased diversity), were significantly higher in CS, due to higher RA of Escherichia-Shigella, Klebsiella and Lactobacillus species. Many of these changes were absent or less pronounced in XS, who exhibited a duodenal luminal microbiome more similar to NS. RA of taxa previously found to be increased in the oral and respiratory microbiota of smokers were also higher in the duodenal luminal microbiome, including Bulledia extructa and an unknown Filifactor species. In conclusion, smoking is associated with an altered duodenal luminal microbiome. However, ex-smokers have a duodenal luminal microbiome that is similar to never-smokers.