bluuebunny/crossref_metadata_2025_split huggingface dataset:
Blood Pressure Trajectories and Outcomes After Endovascular Thrombectomy for Acute Ischemic Stroke
Authors: Katsanos Aristeidis H. , Joundi Raed A. , Palaiodimou Lina , Ahmed Niaz , Kim Joon-Tae , Goyal Nitin , Maier Ilko L. , de Havenon Adam , Anadani Mohammad , Matusevicius Marius , Mistry Eva A. , Khatri Pooja , Arthur Adam S. , Sarraj Amrou , Yaghi Shadi , Shoamanesh Ashkan , Catanese Luciana , Psychogios Marios-Nikos , Tsioufis Konstantinos , Malhotra Konark , Spiotta Alejandro M. , Sandset Else Charlotte , Alexandrov Andrei V. , Petersen Nils H. , Tsivgoulis Georgios 
Published: January 2024

BACKGROUND:
Data on systolic blood pressure (SBP) trajectories in the first 24 hours after endovascular thrombectomy (EVT) in acute ischemic stroke are limited. We sought to identify these trajectories and their relationship to outcomes.

METHODS:
We combined individual-level data from 5 studies of patients with acute ischemic stroke who underwent EVT and had individual blood pressure values after the end of the procedure. We used group-based trajectory analysis to identify the number and shape of SBP trajectories post-EVT. We used mixed effects regression models to identify associations between trajectory groups and outcomes adjusting for potential confounders and reported the respective adjusted odds ratios (aORs) and common odds ratios.

RESULTS:
There were 2640 total patients with acute ischemic stroke included in the analysis. The most parsimonious model identified 4 distinct SBP trajectories, that is, general directional patterns after repeated SBP measurements: high, moderate-high, moderate, and low. Patients in the higher blood pressure trajectory groups were older, had a higher prevalence of vascular risk factors, presented with more severe stroke syndromes, and were less likely to achieve successful recanalization after the EVT. In the adjusted analyses, only patients in the high-SBP trajectory were found to have significantly higher odds of early neurological deterioration (aOR, 1.84 [95% CI, 1.20–2.82]), intracranial hemorrhage (aOR, 1.84 [95% CI, 1.31–2.59]), mortality (aOR, 1.75 [95% CI, 1.21–2.53), death or disability (aOR, 1.63 [95% CI, 1.15–2.31]), and worse functional outcomes (adjusted common odds ratio,1.92 [95% CI, 1.47–2.50]).

CONCLUSIONS:
Patients follow distinct SBP trajectories in the first 24 hours after an EVT. Persistently elevated SBP after the procedure is associated with unfavorable short-term and long-term outcomes.
Optimized Allogenic Decellularized Meniscal Scaffold Modified by Collagen Affinity Stromal Cell–Derived Factor SDF1α for Meniscal Regeneration: A 6- and 12-Week Animal Study in a Rabbit Model
Authors: Zhang Tao , Shi Xin , Li Muzhi , Hu Jianzhong , Lu Hongbin 
Published: January 2024

Background: Total meniscectomy for treating massive meniscal tears may lead to joint instability, cartilage degeneration, and even progressive osteoarthritis. The meniscal substitution strategies for advancing reconstruction of the meniscus deserve further investigation. Hypothesis: A decellularized meniscal scaffold (DMS) modified with collagen affinity stromal cell–derived factor (C-SDF1α) may facilitate meniscal regeneration and protect cartilage from abrasion. Study Design: Controlled laboratory study. Methods: The authors first modified DMS with C-SDF1α to fabricate a new meniscal graft (DMS-CBD [collagen-binding domain]). Second, they performed in vitro studies to evaluate the release dynamics, biocompatibility, and differentiation inducibility (osteogenic, chondrogenic, and tenogenic differentiation) on human bone marrow mesenchymal stem cells. Using in vivo studies, they subjected rabbits that received medial meniscectomy to a transplantation procedure to implement their meniscal graft. At postoperative weeks 6 and 12, the meniscal regeneration outcomes and chondroprotective efficacy of the new meniscal graft were evaluated by macroscopic observation, histology, micromechanics, and immunohistochemistry tests. Results: In in vitro studies, the optimized DMS-CBD graft showed notable biocompatibility, releasing efficiency, and chondrogenic inducibility. In in vivo studies, the implanted DMS-CBD graft after total meniscectomy promoted the migration of cells and extracellular matrix deposition in transplantation and further facilitated meniscal regeneration and protected articular cartilage from degeneration. Conclusion: The new meniscal graft (DMS-CBD) accelerated extracellular matrix deposition and meniscal regeneration and protected articular cartilage from degeneration. Clinical Relevance: The results demonstrate that the DMS-CBD graft can serve as a potential meniscal substitution after meniscectomy.
Age-, season- and gender-specific reference intervals of serum 25-hydroxyvitamin D3 for healthy children (0 ~ 18 years old) in Nanning area of China
Authors: Zhou Dong-yi , Wei Shang-mou , Zhu Chun-ling , Wei Yu-hong , Wang Xiao-mei , Yi Li-ling , Yang Si-tao , Peng Qi-liu 
Published: January 2024

AbstractEstablishing specific reference intervals (RIs) of serum 25-hydroxyvitamin D3 [25(OH)D] for children is essential for improving the accuracy of diagnosis and prognosis monitoring of diseases such as rickets and growth retardation. The study including 6,627 healthy children was conducted to establish specific RIs of 25(OH)D for children in Nanning area of China. The results showed that there were statistically significant differences among age, season, and gender of serum 25(OH)D levels, and the age-specific RIs of serum 25(OH)D were 20.3 ~ 53.6 ng/mL for 0 ~  ≤ 1 year and 18.9 ~ 49.6 ng/mL for 2 ~  ≤ 3 years. The age-, season-specific RIs of serum 25(OH)D for 4 ~  ≤ 6 years in spring–summer and autumn–winter were 15.8 ~ 42.6 ng/mL and 15.2 ~ 37.7 ng/mL, respectively. The age-, gender-specific RIs of serum 25(OH)D for 7 ~  ≤ 18 years for males and females were 12.1 ~ 36.1 ng/mL and 10.8 ~ 35.3 ng/mL, respectively. This study successfully established the RIs of serum 25(OH)D, which may help to improve disease diagnosis and monitoring for children in the Nanning area of China.
GCNFORMER: graph convolutional network and transformer for predicting lncRNA-disease associations
Authors: Yao Dengju , Li Bailin , Zhan Xiaojuan , Zhan Xiaorong , Yu Liyang 
Published: January 2024

Abstract
Background
A growing body of researches indicate that the disrupted expression of long non-coding RNA (lncRNA) is linked to a range of human disorders. Therefore, the effective prediction of lncRNA-disease association (LDA) can not only suggest solutions to diagnose a condition but also save significant time and labor costs.

Method
In this work, we proposed a novel LDA predicting algorithm based on graph convolutional network and transformer, named GCNFORMER. Firstly, we integrated the intraclass similarity and interclass connections between miRNAs, lncRNAs and diseases, and built a graph adjacency matrix. Secondly, to completely obtain the features between various nodes, we employed a graph convolutional network for feature extraction. Finally, to obtain the global dependencies between inputs and outputs, we used a transformer encoder with a multiheaded attention mechanism to forecast lncRNA-disease associations.

Results
The results of fivefold cross-validation experiment on the public dataset revealed that the AUC and AUPR of GCNFORMER achieved 0.9739 and 0.9812, respectively. We compared GCNFORMER with six advanced LDA prediction models, and the results indicated its superiority over the other six models. Furthermore, GCNFORMER's effectiveness in predicting potential LDAs is underscored by case studies on breast cancer, colon cancer and lung cancer.

Conclusions
The combination of graph convolutional network and transformer can effectively improve the performance of LDA prediction model and promote the in-depth development of this research filed.
Identification of eQTLs using different sets of single nucleotide polymorphisms associated with carcass and body composition traits in pigs
Authors: Freitas Felipe André Oliveira , Brito Luiz F. , Fanalli Simara Larissa , Gonçales Janaína Lustosa , da Silva Bruna Pereira Martins , Durval Mariah Castro , Ciconello Fernanda Nery , de Oliveira Camila Sabino , Nascimento Lucas Echevarria , Gervásio Izally Carvalho , Gomes Julia Dezen , Moreira Gabriel Costa Monteiro , Silva-Vignato Bárbara , Coutinho Luiz Lehmann , de Almeida Vivian Vezzoni , Cesar Aline Silva Mello 
Published: January 2024

AbstractBackgroundMapping expression quantitative trait loci (eQTLs) in skeletal muscle tissue in pigs is crucial for understanding the relationship between genetic variation and phenotypic expression of carcass traits in meat animals. Therefore, the primary objective of this study was to evaluate the impact of different sets of single nucleotide polymorphisms (SNP), including scenarios removing SNPs pruned for linkage disequilibrium (LD) and SNPs derived from SNP chip arrays and RNA-seq data from liver, brain, and skeletal muscle tissues, on the identification of eQTLs in theLongissimus lumborumtissue, associated with carcass and body composition traits in Large White pigs. The SNPs identified from muscle mRNA were combined with SNPs identified in the brain and liver tissue transcriptomes, as well as SNPs from the GGP Porcine 50 K SNP chip array. Cis- and trans-eQTLs were identified based on the skeletal muscle gene expression level, followed by functional genomic analyses and statistical associations with carcass and body composition traits in Large White pigs.ResultsThe number of cis- and trans-eQTLs identified across different sets of SNPs (scenarios) ranged from 261 to 2,539 and from 29 to 13,721, respectively. Furthermore, 6,180 genes were modulated by eQTLs in at least one of the scenarios evaluated. The eQTLs identified were not significantly associated with carcass and body composition traits but were significantly enriched for many traits in the “Meat and Carcass” type QTL. The scenarios with the highest number of cis- (n = 304) and trans- (n = 5,993) modulated genes were the unpruned and LD-pruned SNP set scenarios identified from the muscle transcriptome. These genes include 84 transcription factor coding genes.ConclusionsAfter LD pruning, the set of SNPs identified based on the transcriptome of the skeletal muscle tissue of pigs resulted in the highest number of genes modulated by eQTLs. Most eQTLs are of the trans type and are associated with genes influencing complex traits in pigs, such as transcription factors and enhancers. Furthermore, the incorporation of SNPs from other genomic regions to the set of SNPs identified in the porcine skeletal muscle transcriptome contributed to the identification of eQTLs that had not been identified based on the porcine skeletal muscle transcriptome alone.
Single-cell and transcriptomic analyses reveal the influence of diabetes on ovarian cancer
Authors: Zhao Zhihao , Wang Qilin , Zhao Fang , Ma Junnan , Sui Xue , Choe Hyok Chol , Chen Peng , Gao Xue , Zhang Lin 
Published: January 2024

Abstract
Background
There has been a significant surge in the global prevalence of diabetes mellitus (DM), which increases the susceptibility of individuals to ovarian cancer (OC). However, the relationship between DM and OC remains largely unexplored. The objective of this study is to provide preliminary insights into the shared molecular regulatory mechanisms and potential biomarkers between DM and OC.

Methods
Multiple datasets from the GEO database were utilized for bioinformatics analysis. Single cell datasets from the GEO database were analysed. Subsequently, immune cell infiltration analysis was performed on mRNA expression data. The intersection of these datasets yielded a set of common genes associated with both OC and DM. Using these overlapping genes and Cytoscape, a protein‒protein interaction (PPI) network was constructed, and 10 core targets were selected. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were then conducted on these core targets. Additionally, advanced bioinformatics analyses were conducted to construct a TF-mRNA-miRNA coregulatory network based on identified core targets. Furthermore, immunohistochemistry staining (IHC) and real-time quantitative PCR (RT-qPCR) were employed for the validation of the expression and biological functions of core proteins, including HSPAA1, HSPA8, SOD1, and transcription factors SREBF2 and GTAT2, in ovarian tumors.

Results
The immune cell infiltration analysis based on mRNA expression data for both DM and OC, as well as analysis using single-cell datasets, reveals significant differences in mononuclear cell levels. By intersecting the single-cell datasets, a total of 119 targets related to mononuclear cells in both OC and DM were identified. PPI network analysis further identified 10 hub genesincludingHSP90AA1, HSPA8, SNRPD2, UBA52, SOD1, RPL13A, RPSA, ITGAM, PPP1CC, and PSMA5, as potential targets of OC and DM. Enrichment analysis indicated that these genes are primarily associated with neutrophil degranulation, GDP-dissociation inhibitor activity, and the IL-17 signaling pathway, suggesting their involvement in the regulation of the tumor microenvironment. Furthermore, the TF-gene and miRNA-gene regulatory networks were validated using NetworkAnalyst. The identified TFs included SREBF2, GATA2, and SRF, while the miRNAs included miR-320a, miR-378a-3p, and miR-26a-5p. Simultaneously, IHC and RT-qPCR reveal differential expression of core targets in ovarian tumors after the onset of diabetes. RT-qPCR further revealed that SREBF2 and GATA2 may influence the expression of core proteins, including HSP90AA1, HSPA8, and SOD1.

Conclusion
This study revealed the shared gene interaction network between OC and DM and predicted the TFs and miRNAs associated with core genes in monocytes. Our research findings contribute to identifying potential biological mechanisms underlying the relationship between OC and DM.
Inferring single-cell copy number profiles through cross-cell segmentation of read counts
Authors: Liu Furui , Shi Fangyuan , Yu Zhenhua 
Published: January 2024

Abstract
Background
Copy number alteration (CNA) is one of the major genomic variations that frequently occur in cancers, and accurate inference of CNAs is essential for unmasking intra-tumor heterogeneity (ITH) and tumor evolutionary history. Single-cell DNA sequencing (scDNA-seq) makes it convenient to profile CNAs at single-cell resolution, and thus aids in better characterization of ITH. Despite that several computational methods have been proposed to decipher single-cell CNAs, their performance is limited in either breakpoint detection or copy number estimation due to the high dimensionality and noisy nature of read counts data.

Results
By treating breakpoint detection as a process to segment high dimensional read count sequence, we develop a novel method called DeepCNA for cross-cell segmentation of read count sequence and per-cell inference of CNAs. To cope with the difficulty of segmentation, an autoencoder (AE) network is employed in DeepCNA to project the original data into a low-dimensional space, where the breakpoints can be efficiently detected along each latent dimension and further merged to obtain the final breakpoints. Unlike the existing methods that manually calculate certain statistics of read counts to find breakpoints, the AE model makes it convenient to automatically learn the representations. Based on the inferred breakpoints, we employ a mixture model to predict copy numbers of segments for each cell, and leverage expectation–maximization algorithm to efficiently estimate cell ploidy by exploring the most abundant copy number state. Benchmarking results on simulated and real data demonstrate our method is able to accurately infer breakpoints as well as absolute copy numbers and surpasses the existing methods under different test conditions. DeepCNA can be accessed at: https://github.com/zhyu-lab/deepcna.

Conclusions
Profiling single-cell CNAs based on deep learning is becoming a new paradigm of scDNA-seq data analysis, and DeepCNA is an enhancement to the current arsenal of computational methods for investigating cancer genomics.
Genomic evaluation for breeding and genetic management in Cordia africana, a multipurpose tropical tree species
Authors: Ousmael Kedra M. , Cappa Eduardo P. , Hansen Jon K. , Hendre Prasad , Hansen Ole K. 
Published: January 2024

AbstractBackgroundPlanting tested forest reproductive material is crucial to ensure the increased resilience of intensively managed productive stands for timber and wood product markets under climate change scenarios. Single-step Genomic Best Linear Unbiased Prediction (ssGBLUP) analysis is a cost-effective option for using genomic tools to enhance the accuracy of predicted breeding values and genetic parameter estimation in forest tree species. Here, we tested the efficiency of ssGBLUP in a tropical multipurpose tree species,Cordia africana,by partial population genotyping. A total of 8070 trees from three breeding seedling orchards (BSOs) were phenotyped for height. We genotyped 6.1% of the phenotyped individuals with 4373 single nucleotide polymorphisms. The results of ssGBLUP were compared with pedigree-based best linear unbiased prediction (ABLUP) and genomic best linear unbiased prediction (GBLUP), based on genetic parameters, theoretical accuracy of breeding values, selection candidate ranking, genetic gain, and predictive accuracy and prediction bias.ResultsGenotyping a subset of the study population provided insights into the level of relatedness in BSOs, allowing better genetic management. Due to the inbreeding detected within the genotyped provenances, we estimated genetic parameters both with and without accounting for inbreeding. The ssGBLUP model showed improved performance in terms of additive genetic variance and theoretical breeding value accuracy. Similarly, ssGBLUP showed improved predictive accuracy and lower bias than the pedigree-based relationship matrix (ABLUP).ConclusionsThis study ofC. africana, a species in decline due to deforestation and selective logging, revealed inbreeding depression. The provenance exhibiting the highest level of inbreeding had the poorest overall performance. The use of different relationship matrices and accounting for inbreeding did not substantially affect the ranking of candidate individuals. This is the first study of this approach in a tropical multipurpose tree species, and the analysed BSOs represent the primary effort to breedC. africana.
A chromosome-level genome assembly of the Rhus gall aphid Schlechtendalia chinensis provides insight into the endogenization of Parvovirus-like DNA sequences
Authors: Ahmad Aftab , von Dohlen Carol , Ren Zhumei 
Published: January 2024

AbstractThe Rhus gall aphid, Schlechtendalia chinensis, feeds on its primary host plant Rhus chinensis to induce galls, which have economic importance in medicines and the food industry. Rhus gall aphids have a unique life cycle and are economically beneficial but there is huge gap in genomic information about this group of aphids. Schlechtendalia chinensis induces rich-tannin galls on its host plant and is emerging as a model organism for both commercial applications and applied research in the context of gall production by insects. Here, we generated a high-quality chromosome-level assembly for the S. chinensis genome, enabling the comparison between S. chinensis and non-galling aphids. The final genome assembly is 344.59 Mb with 91.71% of the assembled sequences anchored into 13 chromosomes. We predicted 15,013 genes, of which 14,582 (97.13%) coding genes were annotated, and 99% of the predicted genes were anchored to the 13 chromosomes. This assembly reveals the endogenization of parvovirus-related DNA sequences (PRDs) in the S. chinensis genome, which could play a role in environmental adaptations. We demonstrated the characterization and classification of cytochrome P450s in the genome assembly, which are functionally crucial for sap-feeding insects and have roles in detoxification and insecticide resistance. This genome assembly also revealed the whole genome duplication events in S. chinensis, which can be considered in comparative evolutionary analysis. Our work represents a reference genome for gall-forming aphids that could be used for comparative genomic studies between galling and non-galling aphids and provides the first insight into the endogenization of PRDs in the genome of galling aphids. It also provides novel genetic information for future research on gall-formation and insect-plant interactions.
Genome-wide association study of agronomic traits related to nitrogen use efficiency in Henan wheat
Authors: Zhang Zaicheng , Peng Chaojun , Xu Weigang , Li Yan , Qi Xueli , Zhao Mingzhong 
Published: January 2024

Abstract
Background
Nitrogen use efficiency (NUE) is closely related to crop yield and nitrogen fertilizer application rate. Although NUE is susceptible to environments, quantitative trait nucleotides (QTNs) for NUE in wheat germplasm populations have been rarely reported in genome-wide associated study.

Results
In this study, 244 wheat accessions were phenotyped by three NUE-related traits in three environments and genotyped by 203,224 SNPs. All the phenotypes for each trait were used to associate with all the genotypes of these SNP markers for identifying QTNs and QTN-by-environment interactions via 3VmrMLM. Among 279 QTNs and one QTN-by-environment interaction for low nitrogen tolerance, 33 were stably identified, especially, one large QTN (r2 > 10%), qPHR3A.2, was newly identified for plant height ratio in one environment and multi-environment joint analysis. Among 52 genes around qPHR3A.2, four genes (TraesCS3A01G101900, TraesCS3A01G102200, TraesCS3A01G104100, and TraesCS3A01G105400) were found to be differentially expressed in low-nitrogen-tolerant wheat genotypes, while TaCLH2 (TraesCS3A01G101900) was putatively involved in porphyrin metabolism in KEGG enrichment analyses.

Conclusions
This study identified valuable candidate gene for low-N-tolerant wheat breeding and provides new insights into the genetic basis of low N tolerance in wheat.