bluuebunny/crossref_metadata_2025_split huggingface dataset:
Spatial patterns and drivers of soil total nitrogen in anthropogenic shrub encroachment in desert steppe
Authors: Zhao Yanan , Li Zhili , Cao Zhe , Mi Wenbao , Wang Hongmei 
Published: January 2023

Nitrogen is the most important driving factor in primary production and decomposition in arid and semi-arid ecosystems. The effects of shrub encroachment on nitrogen cycling have been investigated at the site scale but seldomly conducted at the landscape scale. Here, we selected 43 shrubland sites distributing across 3000 km2 area in temperate desert grassland in eastern Yanchi County of Ningxia Hui Autonomous. We investigated the spatial heterogeneity and driving factors of soil total nitrogen (STN) at the landscape scale by using geostatistical analysis and the geographical detector method. Our results showed that the average soil total nitrogen decreased in the order of 0–5 cm (0.21 g kg−1) &gt; 5–15 cm (0.19 g kg−1) &gt; 15–40 cm (0.18 g kg−1). Geostatistical analysis showed that soil total nitrogen exhibited the strong spatial autocorrelation in the 0–5 and 5–15 cm soil layers and the moderate spatial autocorrelation in the 15–40 cm soil layer. Furthermore, the geographic detector method indicated that soil physicochemical properties exhibited the stronger effects than these of topographic and vegetation biomass in determining the spatial distribution of soil total nitrogen. Specifically, soil water content in the 0–20 cm soil layer explained 35% of variation in soil total nitrogen spatial pattern in the 0–5 cm soil layer, while soil organic carbon content in the 15–40 cm soil layer explained 64% and 45% of variation in soil total nitrogen spatial patterns in the 5–15 cm and 15–40 cm soil layers, respectively. It was concluded that soil water content and organic carbon content primarily drove the formation of soil total nitrogen spatial heterogeneity in shrubland at the landscape scale, indicating that anthropogenic shrub encroachment evidently affected soil water content and redistribution in dryland.
The first case report of CODAS syndrome in Chinese population caused by two LONP1 pathogenic mutations
Authors: Tang Yi , Liu Yu-Xing , Sheng Yue , Fan Liang-Liang , Zhang Ai-Qian , Zheng Zhao-Fen 
Published: January 2023

Background: CODAS syndrome (MIM 600373) is a multi-system developmental disorder characterized by cerebral, ocular, dental, auricular, and skeletal anomalies. CODAS syndrome is rare in the world and no cases have been reported in Chinese population so far. Mutations in the LONP1 gene can contribute to CODAS syndrome, while the underlying molecular mechanisms requires further investigation.Method: We described a Chinese boy who has suffered from cognition impairment, cataracts, caries, abnormal auricle and skeletal anomalies since birth. The patient’s parents are non-consanguineous and healthy. Whole-exome sequencing (WES) was employed to explore the genetic entity of this family.Results: A compound heterozygous missense mutation (NM_004793: c.2009C&gt;T/p.A670V and c.2014C&gt;T/p.R672C) of LONP1 was identified in the patient. Considering the clinical phenotypes and genetic results, the patient was diagnosed as CODAS syndrome.Conclusion: Here we reported the first case with CODAS syndrome in Chinese population. WES identified a compound heterozygous missense mutation of LONP1 gene in the patients. Our study not only provided data for genetic counseling and clinical diagnosis to this family, but also expanded the clinical spectrum of LONP1-related CODAS syndrome.
An integrative analysis of an lncRNA–mRNA competing endogenous RNA network to identify functional lncRNAs in uterine leiomyomas with RNA sequencing
Authors: Meng Fanfei , Ji Yijing , Chen Xinyu , Wang Yuan , Hua Maofang 
Published: January 2023

Objective: To explore the functions of mRNAs and lncRNAs in the occurrence of uterine leiomyomas (ULs) and further clarify the pathogenesis of UL by detecting the differential expression of mRNAs and lncRNAs in 10 cases of UL tissues and surrounding normal myometrial tissues by high-throughput RNA sequencing.Methods: The tissue samples of 10 patients who underwent hysterectomy for UL in Lianyungang Maternal and Child Health Hospital from January 2016 to December 2021 were collected. The differentially expressed mRNAs (DEmRNAs) and lncRNAs (DElncRNAs) were identified and further analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. The protein–protein interaction network (PPI) was constructed in Cytoscape software. Functional annotation of the nearby target cis‐DEmRNAs of DElncRNAs was performed with the Database for Annotation, Visualization, and Integrated Discovery (DAVID) (https://david.ncifcrf.gov/). Meanwhile, the co-expression network of DElncRNA–DEmRNA was constructed in Cytoscape software.Results: A total of 553 DElncRNAs (283 upregulated DElncRNAs and 270 downregulated DElncRNAs) and 3,293 DEmRNAs (1,632 upregulated DEmRNAs and 1,661 downregulated DEmRNAs) were obtained. GO pathway enrichment analysis revealed that several important pathways were significantly enriched in UL such as blood vessel development, regulation of ion transport, and external encapsulating structure organization. In addition, cytokine–cytokine receptor interaction, neuroactive ligand–receptor interaction, and complement and coagulation cascades were significantly enriched in KEGG pathway enrichment analysis. A total of 409 DElncRNAs–nearby-targeted DEmRNA pairs were detected, which included 118 DElncRNAs and 136 DEmRNAs. Finally, we found that the top two DElncRNAs with the most nearby DEmRNAs were BISPR and AC012531.1.Conclusion: These results suggested that 3,293 DEmRNAs and 553 DElncRNAs were differentially expressed in UL tissue and normal myometrium tissue, which might be candidate-identified therapeutic and prognostic targets for UL and be considered as offering several possible mechanisms and pathogenesis of UL in the future.
Up-regulated PIF1 predicts poor clinical outcomes and correlates with low immune infiltrates in clear cell renal cell carcinoma
Authors: Cai Tong , Wang Ning , Meng Peng , Sun Weigui , Cui Yuanshan 
Published: January 2023

Background: Petite Integration Factor 1 (PIF1) is a multifunctional helicase and DNA processing enzyme that plays an important role in the process of several cancer types. However, the relationship between clear cell renal cell carcinoma (ccRCC) and PIF1 remains unclear. This study aims to explore the role of PIF1 in ccRCC tumorigenesis and prognosis.Methods: Based on The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database, we retrieved and verified the expression of PIF1 in ccRCC tissues as well as normal tissues. To assess the protein expression of PIF1 by using the Human Protein Atlas and the Clinical Proteomic Tumor Analysis Consortium (CPTAC). We also performed receiver operating characteristic (ROC) curve analysis to differentiate the effectiveness of PIF1 in ccRCC and adjacent normal tissues. To evaluate the value of PIF1 on clinical outcomes in ccRCC patients by using multivariate methods and Kaplan‒Meier survival curves. Protein‒protein interaction (PPI) networks were made with STRING. We determined the relationship between the expression of PIF1 and immune cell infiltration with single-sample gene set enrichment analysis (ssGSEA).Results: Compared with normal tissues, the expression of PIF1 was significantly elevated in ccRCC. The mRNA expression of PIF1 is correlated with high TNM stage and high pathologic stage. The receiver operating characteristic (ROC) curve analysis showed that PIF1 was related to an area under the curve (AUC) value of 0.928 to distinguish between ccRCC tissues and normal tissues. Kaplan‒Meier survival analysis showed that the overall survival (OS) of ccRCC patients with a high level of PIF1 was significantly shorter than that of those with a low level of PIF1. PIF1 may play an important role in the occurrence of tumors. Correlation analysis showed that PIF1-mediated carcinogenesis may participate in the process of tumor immune escape in ccRCC.Conclusion: PIF1 could be a reference biomarker to identify ccRCC patients with poor prognosis. PIF1 may play a distinct role in the microenvironment of ccRCC by regulating tumor infiltration of immune cells, which is a new therapeutic target to affect the growth of the tumor.
Identification of the diagnostic genes and immune cell infiltration characteristics of gastric cancer using bioinformatics analysis and machine learning
Authors: Xie Rongjun , Liu Longfei , Lu Xianzhou , He Chengjian , Li Guoxin 
Published: January 2023

Background: Finding reliable diagnostic markers for gastric cancer (GC) is important. This work uses machine learning (ML) to identify GC diagnostic genes and investigate their connection with immune cell infiltration.Methods: We downloaded eight GC-related datasets from GEO, TCGA, and GTEx. GSE13911, GSE15459, GSE19826, GSE54129, and GSE79973 were used as the training set, GSE66229 as the validation set A, and TCGA &amp; GTEx as the validation set B. First, the training set screened differentially expressed genes (DEGs), and gene ontology (GO), kyoto encyclopedia of genes and genomes (KEGG), disease Ontology (DO), and gene set enrichment analysis (GSEA) analyses were performed. Then, the candidate diagnostic genes were screened by LASSO and SVM-RFE algorithms, and receiver operating characteristic (ROC) curves evaluated the diagnostic efficacy. Then, the infiltration characteristics of immune cells in GC samples were analyzed by CIBERSORT, and correlation analysis was performed. Finally, mutation and survival analyses were performed for diagnostic genes.Results: We found 207 up-regulated genes and 349 down-regulated genes among 556 DEGs. gene ontology analysis significantly enriched 413 functional annotations, including 310 biological processes, 23 cellular components, and 80 molecular functions. Six of these biological processes are closely related to immunity. KEGG analysis significantly enriched 11 signaling pathways. 244 diseases were closely related to Ontology analysis. Multiple entries of the gene set enrichment analysis analysis were closely related to immunity. Machine learning screened eight candidate diagnostic genes and further validated them to identify ABCA8, COL4A1, FAP, LY6E, MAMDC2, and TMEM100 as diagnostic genes. Six diagnostic genes were mutated to some extent in GC. ABCA8, COL4A1, LY6E, MAMDC2, TMEM100 had prognostic value.Conclusion: We screened six diagnostic genes for gastric cancer through bioinformatic analysis and machine learning, which are intimately related to immune cell infiltration and have a definite prognostic value.
A four-lncRNA risk signature for prognostic prediction of osteosarcoma
Authors: Liu Huanlong , Chen Chao , Liu Long , Wang Zengtao 
Published: January 2023

Aim: Osteosarcoma is the most common primary malignant tumor of bone. However, our understanding of the prognostic indicators and the genetic mechanisms of the disease progression are still incomplete. The aim of this study was to identify a long noncoding RNA (lncRNA) risk signature for osteosarcoma survival prediction.Methods: RNA sequencing data and relevant clinical information of osteosarcoma patients were downloaded from the database of Therapeutically Applicable Research to Generate Effective Treatments (TARGET). We analyzed the differentially expressed lncRNAs between deceased and living patients by univariate and multivariate Cox regression analysis to identify a risk signature. We calculated a prognostic risk score for each sample according to this prognosis signature, and divided patients into high-risk and low-risk groups according to the median value of the risk score (0.975). Kaplan–Meier analysis and receiver operating characteristic (ROC) curve statistics were used to evaluate the performance of the signature. Next, we analyzed the signature’s potential function through Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene-set enrichment analysis (GSEA). Lastly, qRT-PCR was used to validate the expression levels of the four lncRNAs in clinical samples.Results: Twenty-six differentially expressed lncRNAs were identified between deceased and living patients. Four of these lncRNAs (CTB-4E7.1, RP11-553A10.1, RP11-24N18.1, and PVRL3-AS1) were identified as independent prognostic factors, and a risk signature of these four lncRNAs for osteosarcoma survival prediction was constructed. Kaplan–Meier analysis showed that the five-year survival time in high-risk and low-risk groups was 33.1% and 82.5%, and the area under the curve (AUC) of the ROC was 0.784, which demonstrated that the prognostic signature was reliable and had the potential to predict the survival of patients with osteosarcoma. The expression level of the four lncRNAs in osteosarcoma tissues and cells was determined by qRT-PCR. Functional enrichment analysis suggested that the signature might be related to osteosarcoma through regulation of the MAPK signaling pathway, the PI3K-Akt signaling pathway, and the extracellular matrix and also provided new insights into the study of osteosarcoma, including the role of papillomavirus infection, olfactory receptor activity, and olfactory transduction in osteosarcoma.Conclusion: We constructed a novel lncRNA risk signature that served as an independent biomarker for predicting the prognosis of osteosarcoma patients.
Bioinformatic analysis and machine learning to identify the diagnostic biomarkers and immune infiltration in adenomyosis
Authors: Liu Dan , Yin Xiangjie , Guan Xiaohong , Li Kunming 
Published: January 2023

Background: Adenomyosis is a hormone-dependent benign gynecological disease characterized by the invasion of the endometrium into the myometrium. Women with adenomyosis can suffer from abnormal uterine bleeding, severe pelvic pain, and subfertility or infertility, which can interfere with their quality of life. However, effective diagnostic biomarkers for adenomyosis are currently lacking. The aim of this study is to explore the mechanism of adenomyosis by identifying biomarkers and potential therapeutic targets for adenomyosis and analyzing their correlation with immune infiltration in adenomyosis.Methods: Two datasets, GSE78851 and GSE68870, were downloaded and merged for differential expression analysis and functional enrichment analysis using R software. Weighted gene co-expression network analysis (WGCNA), the least absolute shrinkage and selection operator (LASSO), and support vector machine-recursive feature elimination (SVE-RFE) were combined to explore candidate genes. Quantitative reverse transcriptase PCR (qRT-PCR) was conducted to verify the biomarkers and receiver operating characteristic curve analysis was used to assess the diagnostic value of each biomarker. Single-sample Gene Set Enrichment Analysis (ssGSEA) and CIBERSORT were used to explore immune cell infiltration in adenomyosis and the correlation between diagnostic biomarkers and immune cells.Results: A total of 318 genes were differentially expressed. Through the analysis of differentially expressed genes and WGCNA, we obtained 189 adenomyosis-related genes. After utilizing the LASSO and SVM-RFE algorithms, four hub genes, namely, six-transmembrane epithelial antigen of the prostate-1 (STEAP1), translocase of outer mitochondrial membrane 20 (TOMM20), glycosyltransferase eight domain-containing 2 (GLT8D2), and NME/NM23 family member 5 (NME5) expressed in nucleoside-diphosphate kinase, were identified and verified by qRT-PCR. Immune infiltration analysis indicated that T helper 17 cells, CD56dim natural killer cells, monocytes, and memory B-cell may be associated with the occurrence of adenomyosis. There were significant correlations between the diagnostic biomarkers and immune cells.Conclusion: STEAP1, TOMM20, GLT8D2, and NME5 were identified as potential biomarkers and therapeutic targets for adenomyosis. Immune infiltration may contribute to the onset and progression of adenomyosis.
Case report: Therapy adherence, MTTP variants, and course of atheroma in two patients with HoFH on low-dose, long-term lomitapide therapy
Authors: Kayikcioglu Meral , Ozkan Hasan Selcuk , Yagmur Burcu , Bayraktaroglu Selen , Vardarli Asli Tetik 
Published: January 2023

Background: Homozygous familial hypercholesterolemia (HoFH) is a rare and devastating genetic condition characterized by extremely elevated levels of low-density lipoprotein cholesterol (LDL-C) leading to an increased risk of premature atherosclerosis. Patients with Homozygous familial hypercholesterolemia mostly present with mutations in LDLR; however, herein, we present two cases with concomitant microsomal triglyceride transfer protein mutations, who showed different clinical courses and treatment adherence on long-term therapy with the new MTTP inhibitor lomitapide.Objectives: We aimed to present the possibility of preventing the progression of atherosclerotic burden with effective and safe LDL-C reduction in patients with Homozygous familial hypercholesterolemia on low-dose lomitapide therapy and emphasize the role of treatment adherence in therapy success.Methods: We present two patients with phenotypically Homozygous familial hypercholesterolemia, a compound heterozygous woman and a simple homozygous man, both with LDLR and additional MTTP mutations, who were treated with the MTTP-inhibiting agent lomitapide, with different treatment compliances. The role of impulsivity was investigated through Barratt Impulsivity Scale 11, and the extent of the atherosclerotic burden was followed up using coronary artery calcium scoring, echocardiographic and sonographic findings, and, eventually, through a strict follow-up of laboratory parameters. The patients were on lomitapide for 8 and 5 years, respectively, with no adverse effects.Conclusion: When accompanied by good adherence to therapy, low-dose lomitapide on top of standard lipid-lowering therapy with decreased frequency of lipid apheresis prevented the progression of atherosclerotic burden. Non-compliance might occur due to patient impulsivity and non-adherence to a low-fat diet.
Identification of a nucleotide metabolism-related signature to predict prognosis and guide patient care in hepatocellular carcinoma
Authors: Li Yu , Wu Chunyan , Ge Yingnan , Chen Xi , Zhu Li , Chu Ling , Wang Jia , Yan Meiling , Deng Hao 
Published: January 2023

Background: Hepatocellular carcinoma is a highly malignant tumor with significant heterogeneity. Metabolic reprogramming plays an essential role in the progression of hepatocellular carcinoma. Among them, nucleotide metabolism needs further investigation.Methods: Based on the bioinformatics approach, eleven prognosis-related nucleotide metabolism genes of hepatocellular carcinoma were screened in this study. Based on the Lasso-Cox regression method, we finally identified a prognostic model containing six genes and calculated the risk score for each patient. In addition, a nomogram was constructed on the basis of pathological stage and risk score.Results: Patients with high-risk score had worse prognosis than those with low-risk. The predictive efficiency of the model was efficient in both the TCGA dataset and the ICGC dataset. The risk score is an independent prognostic factor that can be used to screen chemotherapy drugs. In addition, the risk score can be useful in guiding patient care at an early stage.Conclusion: Nucleotide metabolism-related prognostic model can more accurately predict the prognosis of patients with hepatocellular carcinoma. As a novel prediction model, it is expected to help clinical staff to provide targeted treatment and nursing to patients.
Novel variants of NEK9 associated with neonatal arthrogryposis: Two case reports and a literature review
Authors: Liu Fang , Dai Liying , Li Zhi , Yin’s Xiaowei 
Published: January 2023

Objective: Pathogenic variants in NEK9 (MIM: 609798) have been identified in patients with lethal congenital contracture syndrome 10 (OMIM: 617022) and arthrogryposis, Perthes disease, and upward gaze palsy (APUG and OMIM: 614262). The shared core phenotype is multiple joint contractures or arthrogryposis. In the present study, three novel variants of NEK9 associated with neonatal arthrogryposis were reported.Methods: The clinical data of two premature infants and their parents were collected. The genomic DNA was extracted from their peripheral blood samples and subjected to trio-whole-exome sequencing (trio-WES) and copy number variation analysis.Results: Using trio-WES, a total of three novel pathogenic variants of NEK9 were detected in the two families. Patient 1 carried compound heterozygous variations of c.717C &gt; A (p. C239*741) and c.2824delA (p.M942Cfs*21), which were inherited from his father and mother, respectively. Patient 2 also carried compound heterozygous variations of c.61G &gt; T (p. E21*959) and c. 2824delA (p. M942Cfs*21), which were inherited from his father and mother, respectively. These variants have not been previously reported in the ClinVar, HGMD, or gnomAD databases.Conclusion: This is the first report about NEK9-related arthrogryposis in neonatal patients. The findings from this study suggest that different types of mutations in NEK9 lead to different phenotypes. Our study expanded the clinical phenotype spectrum and gene spectrum of NEK9-associated arthrogryposis.
Conventional dendritic cells type 1 are strongly enriched, quiescent and relatively tolerogenic in local inflammatory arthritis
Authors: Boltjes Arjan , Samat Anoushka Ashok Kumar , Plantinga Maud , Mokry Michal , Castelijns Bas , Swart Joost F. , Vastert Sebastiaan J. , Creyghton Menno , Nierkens Stefan , van Loosdregt Jorg , van Wijk Femke 
Published: January 2023

IntroductionDendritic cells (DC) are crucial for initiating and shaping immune responses. So far, little is known about the functional specialization of human DC subsets in (local) inflammatory conditions. We profiled conventional (c)DC1, cDC2 and monocytes based on phenotype, transcriptome and function from a local inflammatory site, namely synovial fluid (SF) from patients suffering from a chronic inflammatory condition, Juvenile Idiopathic Arthritis (JIA) as well as patients with rheumatoid arthritis (RA).MethodsPaired PB and SF samples from 32 JIA and 4 RA patients were collected for mononuclear cell isolation. Flow cytometry was done for definition of antigen presenting cell (APC) subsets. Cell sorting was done on the FACSAria II or III. RNA sequencing was done on SF APC subsets. Proliferation assays were done on co-cultures after CD3 magnetic activated cell sorting (MACS). APC Toll-like receptor (TLR) stimulation was done using Pam3CSK4, Poly(I:C), LPS, CpG-A and R848. Cytokine production was measured by Luminex.ResultscDC1, a relatively small DC subset in blood, are strongly enriched in SF, and showed a quiescent immune signature without a clear inflammatory profile, low expression of pathogen recognition receptors (PRRs), chemokine and cytokine receptors, and poor induction of T cell proliferation and cytokine production, but selective production of IFNλ upon polyinosinic:polycytidylic acid exposure. In stark contrast, cDC2 and monocytes from the same environment, showed a pro-inflammatory transcriptional profile, high levels of (spontaneous) pro-inflammatory cytokine production, and strong induction of T cell proliferation and cytokine production, including IL-17. Although the cDC2 and monocytes showed an overlapping transcriptional core profile, there were clear differences in the transcriptional landscape and functional features, indicating that these cell types retain their lineage identity in chronic inflammatory conditions.DiscussionOur findings suggest that at the site of inflammation, there is specific functional programming of human DCs, especially cDC2. In contrast, the enriched cDC1 remain relatively quiescent and seemingly unchanged under inflammatory conditions, pointing to a potentially more regulatory role.