bluuebunny/crossref_metadata_2025_split huggingface dataset:
Project Happy Apples: A medical student-initiated community project for normalizing conversations about death in Singapore
Authors: Low Chen Ee , Rana Sounak , Yau Chun En , Tan Sheryl Yen Pin , Chan Noreen , Lim Mervyn Jun Rui 
Published: August 2023

Abstract
Introduction:
A 2014 survey of the Singaporean population revealed just 50% had awareness of palliative care. In the last decade, Project Happy Apples (PHA), a medical-student-led project, had supported palliative-care patients, empowered future doctors, and prepared society for end-of-life care. We aim to assess the efficacy of PHA’s public exhibition in improving attitudes, knowledge, and perception of palliative care amongst the Singaporean public.
Methods
An anonymous, cross-sectional survey was conducted on participants in PHA’s 2022 exhibition via scanning a QR code.
Results
During the 2022 exhibition, there were 208 respondents. Statistically significant improvements in familiarity (pre-exhibition β = 2.89, post-exhibition β = 3.89, P < 0.001), understanding of issues surrounding palliative care (pre-exhibition β = 3.04, post-exhibition β = 3.91, P < 0.001), and comfort level when talking about death (pre-exhibition β = 3.48, post-exhibition β = 3.91, P < 0.001) were reported following the exhibition.
Conclusion
PHA’s public exhibition was effective in raising familiarity, comfort and understanding of palliative care among the Singaporean public.
Radiographic assessment of soft tissue changes with PEEK onlay versus conventional osteotomy protocol in advancement genioplasty: A randomized clinical trial
Authors: Monim Ghada Abdel , Chehata Ingy Mohamed , Shawky Mohamed , Mounir Mohamed , Atef Mohammed 
Published: August 2023

Abstract
Background The breakthroughs in virtual planning and computer guided surgeries improved the accuracy and predictability of guided surgical procedures and enhanced the use of patient specific implants. The aim of this study was to describe a radiographic method for assessment of soft tissue gain with patient specific PEEK chin implants versus computer guided advancement genioplasty in patients with retruded chins.Materials and methods Patients with retruded chins indicated for corrective genioplasty were recruited and randomly allocated into two equal groups; Group A received a patient specific onlay PEEK chin implant, while group B received fully computer guided advancement genioplasty. The preoperative and the one-year postoperative CT scans were superimposed and the 3D generated soft tissue contours were compared.Results Each group included ten patients. The mean amount of chin advancement in the osteotomy group was 8.12 mm ± 0.69 which was significantly higher than 5.22 mm ± 1.18 for the PEEK group. The mean one-year soft tissue gain in the osteotomy group was 7.63 mm ± 0.49 which was also significantly higher than 3.72 mm ± 1.7 for the PEEK group.Conclusion Radiographic soft tissue assessment is a reliable way of evaluation of soft tissue changes. Also, Computer guided advancement genioplasty could provide better net soft tissue gain than PEEK chin implants.Clinical relevance: This study emphasized the reliability of CT based soft tissue assessment and set the base for using facial laser scanning in future studies. It also proved that autogenous genioplasty is still the gold standard.
Analysis of the Dynamic Relationship between Construction Industry Development and Environmental Pollution in Liaoning Province Based on VAR Modeling
Authors: Qi Yuan , Xu Li , Jiang Lei 
Published: August 2023

Abstract
Liaoning Province is a large province of the construction industry in Northeast China. To achieve the high-quality development of the construction industry in Liaoning Province, this paper selects the data of six environmental pollution indicators in Liaoning Province from 2000 to 2020 to measure and analyze, which are the total economic output value of the construction industry, industrial sulfur dioxide emissions, industrial smoke and dust emissions, industrial wastewater emissions, industrial solid waste generation, and carbon emissions from the construction industry. Based on the vector autoregressive (VAR) model, this paper first analyzes the long-term evolution of the relationship between the economic growth of the construction industry and each environmental pollution indicator, then empirically analyzes the dynamic econometric relationship between the economic growth of the construction industry and the environmental pollution in Liaoning Province through impulse response analysis and variance decomposition. The results show that each environmental pollution indicator has different degrees of influence on the construction industry economy. Among them, industrial sulfur dioxide emissions and industrial smoke and dust emissions have an inhibitory effect on the growth of the construction industry economy, while construction carbon emissions have a promotional effect on the growth of the construction industry economy. Combined with the analysis of the results of the VAR model, corresponding countermeasures and suggestions are put forward from the perspective of the transformation and upgrading of the construction industry in Liaoning Province.
High Neutrophil-to-Lymphocyte Ratio Predicts Stroke-Associated Pneumonia in Intracerebral Hemorrhage A Propensity Score Matching Analysis
Authors: Lu Hong-Ji , Wang Rui-Hong , Yuan Fang , Li Hui-Ping , Ma Zhao-Hui , Wu Shi-Biao , Lu Ai-Li , Wen Wan-Xin , Huang Yan , Wang Li-Xin 
Published: August 2023

Abstract
Background Inflammatory mechanisms play important roles in intracerebral hemorrhage (ICH) and have been linked to the development of stroke-associated pneumonia (SAP). The neutrophil-to-lymphocyte ratio (NLR) is an inflammatory index that reflects systemic inflammatory responses after stroke. In this study, we aimed to evaluate the predictive value of the NLR for SAP and ICU admission in patients with ICH.Methods Patients with ICH in four hospitals were prospectively enrolled. Data on the NLR were collected at admission, and the correlation between these factors and the clinical pulmonary infection score (CPIS) was assessed through Spearman’s analysis. Outcomes at discharge were collected and assessed by the modified Rankin scale (mRS). Propensity score matching (PSM) analysis was used to compare outcomes between the groups.Results A total of 320 patients were enrolled in this study, among whom 126 (39.4%) developed SAP. A total of 176 patients were enrolled in the PSM cohort, among whom 66 (37.5%) developed SAP. The results of the receiver operating characteristic (ROC) analysis revealed that the NLR had predictive value for SAP in both the original cohort (AUC: 0.748, 95% CI: 0.695–0.801) and PSM cohort (AUC: 0.657, 95% CI: 0.575–0.739). The NLR also predicted ICU admission in both the original cohort (AUC: 0.732, 95% CI: 0.671–0.786) and the PSM cohort (AUC: 0.646, 95% CI: 0.563–0.723). The NLR remained significant after adjusting for other confounders in the multivariable analysis in both the original cohort (adjusted OR = 1.090, 95% CI: 1.029–1.155, P = 0.003) and PSM cohort (adjusted OR = 1.057, 95% CI, 1.004–1.113, P = 0.034). Spearman’s analysis showed that the NLR was correlated with the CPIS in both the original cohort (r = 0.537, 95% CI: 0.395–0.654) and PSM cohort (r = 0.504, 95% CI: 0.292–0.669). ROC curve analysis also showed that the NLR predicted poor outcomes at discharge in both the original cohort (AUC: 0.761, 95% CI: 0.707–0.815) and the PSM cohort (AUC: 0.584, 95% CI: 0.500–0.670).Conclusions A high NLR value at admission predicted SAP in patients with ICH, and the best cutoff value was 6.06. The NLR also contributed to predicting severe SAP and ICU admission. Patients with higher NLR levels had higher in-hospital mortality and poorer outcomes at discharge.
A Two-Phase Deep Learning Approach to Glaucoma Estimation Using Retinal Layers Thickness
Authors: Xu Linchuan , Asaoka Ryo , Cao Jiannong , Murata Hiroshi , Fujino Yuri , Yamanishi Kenji 
Published: August 2023

Abstract
Glaucoma, which makes progressive and irreversible sight damage to human eyes, is the second leading cause of blindness worldwide. The damage is principally estimated by visual field (VF) sensitivity through costly visual field tests. To achieve a less costly estimation, a promising method is to first measure retinal layers thickness (RT) by optical coherence tomography and then map RT into VF. There are some recent studies showing that the mapping can be effectively learned by convolutional neural networks (CNNs). However, different stages of glaucoma, e.g., early stage and severe stage, that result in different relations between VF and RT, have not yet been distinguished in the learning. Consequently, the learned mapping may be a poor fit for each of these stages especially when training data are small-scale. In this paper we propose for the first time an approach that distinguishes two different glaucoma stages in learning the mapping. In particular, our approach is two-phase, the first of which is to estimate the probability of an RT being a particular stage and the second is to learn stage-specific mappings. For the probability estimation, we employ a CNN based classification model. We design a set of data augmentation techniques for training as well as a test-time augmentation technique for testing by referring to the domain knowledge of the data. To learn stage-specific mappings, we design a regression model with a novel two-branch architecture. Moreover, we introduce a novel attention mechanism to CNN for both the classification and the regression. Through experiments on a real-world dataset, we demonstrate that our proposed method outperforms existing methods by 6.82% in terms of mean of the root mean square error for early stage of glaucoma.
Emerging potential of spinach PGPR for plant growth promotion
Authors: Bashir Sadia , Marium Hifza , Haroon Adeela 
Published: August 2023

Abstract

The quest for enhancing the production of leafy vegetables due to their high nutritional status has led to inevitable use of hazardous agrochemicals leading to chief agricultural losses. Plant growth promoting rhizobacteria (PGPR) being harmless biofertilizers can serve as suitable candidates for attaining the increasing demands of global agriculture. With perspective to explore the bio efficiency of Spinach oleracea rhizobacteria, the study was designed utilizing rhizospheric bacteria of spinach. Initially, seventeen rhizobacteria (ST1, ST2, ST4, ST5, ST7, ST8, ST11, ST12, ST14, ST15, ST16, ST17, ST18, ST19, ST20, ST23, ST25) were isolated which were identified morphologically. Subsequent biochemical testing revealed their identification as Bacillus spp, Clostridium spp, Corynebacterium spp, Lactobacillus spp and Mycobacterium spp. The Screening of these isolates for multiple PGP traits exposed their potentialities. However, employment of most potential PGPR at two varieties (Desi palak and Lahori Palak) of spinach further confirmed their putative role in growth enhancement of spinach. Therefore, current results suggest the significant application of spinach associated rhizoflora as safer and effective biofertilizers for extendable agricultural land.
Identification of key lncRNAs and mRNAs related intramuscular fat in pigs by WGCNA
Authors: Li Wenqiang , Yang Suozhou , Liu Huixin , Cao Zhi , Xu Fei , Ning Chao , Zhang Qin , Wang Dan , Tang Hui 
Published: August 2023

Abstract
Background: Intramuscular fat (IMF) is an important indicator of pork quality, whose content directly affects the tenderness, juiciness and other flavour traits of pork, and it also influences consumers' choice of pork. Long non-coding RNA (lncRNA) plays an important role as key regulators in IMF deposition, but its function and characteristics in IMF deposition are not fully understood. Weighted gene co-expression network analysis (WGCNA) is an accurate and powerful method for studying gene interactions of quantitative traits, but so far, there is no report on weighted gene co-expression network analysis on the regulation of fat deposition in porcine muscle based on both mRNA and lncRNA datasets. Therefore, this study aimed to construct an mRNA-lncRNA co-expression network using WGCNA to mine and identify potential candidate genes affecting IMF deposition in pigs.
Results: We used whole-transcriptome sequencing data generated from 31 longest dorsal muscle tissues of Yimeng Black pigs to construct a gene expression matrix containing 8093 mRNAs and 198 lncRNAs. A total of nine co-expression modules were identified using the WGCNA method, of which the magenta and turquoise modules were significantly associated with IMF deposition. We identified 15 mRNAs and 4 lncRNAs as key genes that might play an important role in the regulation of IMF deposition.
Conclusions: This study used WGCNA to construct a lncRNA-mRNA co-expression network and reveal key genes that regulate intramuscular fat deposition and to construct lncRNA-mRNA-pathway network. We provided new insights into the complex biology of IMF deposition in pigs and may help to improve pork quality.
Utilizing transcriptomics and metabolomics to unravel key genes and metabolites of maize seedlings in response to drought stress
Authors: Li Yipu , Su Zhijun , Lin Yanan , Xu Zhenghan , Bao Haizhu , Wang Fugui , Liu Jian , Hu Shuping , Wang Zhigang , Yu Xiaofang , Gao Julin 
Published: August 2023

Abstract

Background
Drought stress can substantially restrict maize growth and productivity, and global warming and an increasing frequency of extreme weather events are likely to result in more yield losses in the future. Therefore, unraveling the molecular mechanism underlying the response to drought stress is essential for breeding drought-resilient crops.
Results
In this study, we subjected the 3-leaf-period plants of two maize inbred lines, a drought-tolerant line (si287) and a drought-sensitive line (X178), to drought stress for seven days while growing in a chamber. Subsequently, we measured physiological traits and analyzed transcriptomic and metabolic profiles of two inbred lines. Our KEGG analysis of genes and metabolites revealed significant differences in pathways related to glycolysis/gluconeogenesis, flavonoid biosynthesis, starch and sucrose metabolism, and biosynthesis of amino acids. Our joint analysis identified proline, tryptophan and phenylalanine are crucial amino acids for maize response to drought stress. Especially, tryptophan (Trp) was found to enhance tolerance via IAA and ABA signaling and flavonoid biosynthesis. We identified three hub genes, indole-3-acetaldehyde oxidase (ZmAO1, 542228), catalase 1 (ZmCAT1, 542369), and flavin-containing monooxygenase 6 (ZmYUC6, 103629142), that may regulate tryptophan biosynthesis and drought tolerance. Genes and metabolites related to tryptophan biosynthesis, such as L-tryptophan, indole, and shikimic acid, represent potential targets for genome editing to improve maize tolerance and yield under drought stress.
Conclusions
This study sheds light on the molecular mechanisms of maize seedlings in response to drought stress and identifies candidate genes and metabolites for improving drought tolerance in maize. The identification of different resistance mechanisms in maize inbred lines will facilitate the exploration of maize germplasm and the breeding of drought-resilient varieties.
Parent-child couples display shared neural fingerprints while listening to stories: A functional magnetic resonance study
Authors: Habouba Nir , Talmon Ronen , Kraus Dror , Farah Rola , Apter Alan , Steinberg Tamar , Radhakrishnan Rupa , Barazany Daniel , Horowitz-Kraus Tzipi 
Published: August 2023

Abstract
Neural fingerprinting is a method to identify individuals from a group of people. Here we established a new connectome-based identification model and used diffusion maps to show that biological parent-child couples share functional connectivity patterns while listening to stories. These shared fingerprints enabled identifying children and their biological parents from a group of parents and children. Functional patterns were evident in both cognitive and sensory brain networks. Defining “typical” shared biological parent-child brain patterns may enable predicting or even preventing impaired parent-child connections that develop due to genetic or environmental causes. Finally, we argue that the proposed framework opens new opportunities to link similarities in connectivity patterns to behavioral, psychological, and medical phenomena among other populations. To our knowledge, this is the first study to reveal the neural fingerprint that represents distinct biological parent-child couples.
Unemployment: Automation, Monopolistic and Bargaining Power
Authors: Yılmaz Ensar , Vardar Nevzat Barış 
Published: August 2023

Abstract
In this study, we mainly focus on the linkages between automation and unemployment under other unemployment generating structural mechanisms, which arise out of monopolistic power of firms in goods market and union power in labor market. For this, we construct a static general equilibrium model with a two-sector framework. Penetration of automation creates a widespread spillover effects on unemployment, wages of workers having different skill levels, resource allocation and income inequality. The existence of monopolistic power and union bargaining affects the way in which automation affects the variables of interest, in particular unemployment. It seems that automation turns out to be very good for growth and very bad for employment and equality.
JEL Classication: O33, J63, J64, D30, J51
Comprehensive analysis of single-cell transcriptome and bulk transcriptome sequencing identifies B cell-related biomarkers in obesity
Authors: Chen Jiankun , Li Zuming , Huang Bin , Feng Jieni , Xie Changcai , Cai Shubin , Li Jiqiang , Lu Yue , Chen Yu 
Published: August 2023

Abstract
Background: Obesity represents a significant public health concern，B cells residing in adipose tissue have been found to be closely associated with weight gain, metabolic dysfunction, and inflammation in individuals with obesity. Nevertheless, the precise contribution of B cells to the development of obesity remains uncertain. In this study, RNA-seq and single-cell RNA sequencing (scRNA-seq) data were combined to explore the molecular mechanisms of B cell involvement in obesity and identify B cell-related biomarkers.
Methods: Obesity scRNA-seq and Bulk sequences were downloaded from the GEO database. The scRNA-seq data processing was performed using the R software package "Seurat" and downscaling and cluster identification were performed using UMAP. The FindAllMarkers function is used to identify the marker genes for each cluster. B cell clusters in the dataset were further clustered by PCA, UMAP, and SNN. GO and KEGG analyzed the differential genes of four B cell subtypes. iTALK is used to analyze communication molecules between B cell subsets. Obesity-related differentially expressed genes (DEGs) were obtained by limma software package. Further, LASSO and CytoHubba were used to identify B cell-related biomarkers in obesity. The expression of B cell-related biomarkers was confirmed by RT-PCR in the animal model induced by high-fat diet.
Results:Analysis of scRNA-seq data identified 28 cell subpopulations and 9 core cell types. B cells were significantly down-regulated in the obese group compared to the control group. At the same time B cells re-clustered into 10 clusters and they eventually clustered into 4 types, namely Exhausted B cells, Naive B cells, Non-switched memory B cells, and Plasmablasts. We identified 790 B-cell differentially expressed genes from the scRNA-seq dataset and 928 obesity-related differentially expressed genes from the Bulk RNA-seq dataset, and after cross-analysis, CytoHubba and LASSO analysis, we obtained 3 B cell-related biomarkers (GAPDH, AHNAK, HEXIM1). Animal experiments confirmed the expression of three B cell-related biomarkers in obesity.
Conclusions: This study revealed the pathogenesis of B cells in obesity and also suggest that 3 B cell-related biomarkers (GAPDH, AHNAK, and HEXIM1) may be promising therapeutic targets in the future obesity therapeutic field.
Woodland birds benefit from suppression of a despotic competitor following creation of artificial ‘sink’ habitat through culling
Authors: Barati Ahmad , McDonald Paul G. 
Published: August 2023

AbstractContext While habitat fragmentation negatively impacts native biodiversity, this ecological process can be beneficial for edge-specialist species that preferentially occupy remnant patches. In the eastern woodlands of Australia, this process leads to the despotic Noisy Miner (Manorina melanocephala) dominating remnant patches and aggressively excluding other avifauna. Culling has been trialled in attempt to alleviate the impacts of Noisy Miners, however has yielded mixed success in the short-term as recolonising miners from the surrounding areas rapidly occupy newly culled sites. Objectives We tested if ongoing, continuous removal of Noisy Miners from one site could create an artificial ‘sink’ habitat that would allow more efficient management of recolonisation reduction and allow native woodland bird recovery in other areas. Methods Over 18 months, Noisy Miners were removed from two sites on a regular basis and the changes in the miner density and avian diversity were assessed. Results At one site, birds routinely recolonised newly created vacant ‘sink’ areas following a culling round, therfore miner density at this site was not impacted long-term. In contrast, a nearby area was not effectively recolonised and was kept miner-free for more than one year, concurrently experiencing a rebound in avian diversity. Conclusions Together, these results suggest that as well as being more feasible logistically, conducting ongoing longer-term culling at highly favoured sites is likely to be a more effective and logistically simpler management strategy than repeated, separate short-term culling events at a range of habitats, offering an additional model for the management of overabundant, despotic species.