bluuebunny/crossref_metadata_2025_split huggingface dataset:
Outcomes of hemi- vs. total arch replacement in acute type A aortic dissection: A systematic review and meta-analysis
Authors: Ma Likang , Chai Tianci , Yang Xiaojie , Zhuang Xinghui , Wu Qingsong , Chen Liangwan , Qiu Zhihuang 
Published: September 2022

BackgroundAcute type A aortic dissections (ATAAD) pose a challenge to surgeons due to high mortality, and decision making regarding the appropriate procedure is controversial. This study compared the outcomes of hemiarch and total arch replacement for ATAAD.MethodsThe PubMed, Web of Science, Embase and Cochrane databases were searched for comparative studies on hemiarch versus total arch replacement that were published before May 1, 2022.ResultsWe included 23 observational studies with a total of 4,576 patients. Combined data analysis showed that early mortality (RR = 0.82; 95% CI: 0.70–0.97; P = 0.02), incidence of postoperative permanent neurological dysfunction (RR = 0.72; 95%CI:0.54∼0.94; P = 0.02), and incidence of renal failure and dialysis (RR = 0.82; 95%CI:0.71∼0.96; P = 0.01) were all lower for hemiarch than for total arch replacement. However, hemiarch replacement had a higher rate of late mortality (RR = 1.37; 95%CI:1.10∼1.71; P = 0.005). There were no statistically significant differences between the two groups in terms of re-operation for bleeding, aortic re-operation, or postoperative pneumonia.ConclusionIn this study, hemiarch replacement had better early outcomes but a higher late mortality rate than total arch replacement. Decisions regarding the extent of arch repair should be made according to location and extent of ATAAD and the experience of surgeons to ensure the most favorable prognosis.Systematic review registration:[INPLASY.COM], identifier [INPLASY202250088].
Identification of benign and malignant thyroid nodules based on dynamic AI ultrasound intelligent auxiliary diagnosis system
Authors: Wang Bing , Wan Zheng , Li Chen , Zhang Mingbo , Shi YiLei , Miao Xin , Jian Yanbing , Luo Yukun , Yao Jing , Tian Wen 
Published: September 2022

BackgroundDynamic artificial intelligence (AI) ultrasound intelligent auxiliary diagnosis system (Dynamic AI) is a joint application of AI technology and medical imaging data, which can perform a real-time synchronous dynamic analysis of nodules. The aim of this study is to investigate the value of dynamic AI in differentiating benign and malignant thyroid nodules and its guiding significance for treatment strategies.MethodsThe data of 607 patients with 1007 thyroid nodules who underwent surgical treatment were reviewed and analyzed, retrospectively. Dynamic AI was used to differentiate benign and malignant nodules. The diagnostic efficacy of dynamic AI was evaluated by comparing the results of dynamic AI examination, preoperative fine needle aspiration cytology (FNAC) and postoperative pathology of nodules with different sizes and properties in patients of different sexes and ages.ResultsThe sensitivity, specificity and accuracy of dynamic AI in the diagnosis of thyroid nodules were 92.21%, 83.20% and 89.97%, respectively, which were highly consistent with the postoperative pathological results (kappa = 0.737, p &lt; 0.001). There is no statistical difference in accuracy between people with different ages and sexes and nodules of different sizes, which showed the good stability. The accuracy of dynamic AI in malignant nodules (92.21%) was significantly higher than that in benign nodules (83.20%) (p &lt; 0.001). The specificity and positive predictive value were significantly higher, and the misdiagnosis rate was significantly lower in dynamic AI than that of preoperative ultrasound ACR TI-RADS (p &lt; 0.001). The accuracy of dynamic AI in nodules with diameter ≤ 0.50 cm was significantly higher than that of preoperative ultrasound (p = 0.044). Compared with FNAC, the sensitivity (96.58%) and accuracy (94.06%) of dynamic AI were similar.ConclusionsThe dynamic AI examination has high diagnostic value for benign and malignant thyroid nodules, which can effectively assist surgeons in formulating scientific and reasonable individualized diagnosis and treatment strategies for patients.
Assessing the intracellular primary metabolic profile of Trichoderma reesei and Aspergillus niger grown on different carbon sources
Authors: Borin Gustavo Pagotto , Oliveira Juliana Velasco de Castro 
Published: September 2022

Trichoderma reesei and Aspergillus niger are efficient biological platforms for the production of various industrial products, including cellulases and organic acids. Nevertheless, despite the extensive research on these fungi, integrated analyses of omics-driven approaches are still missing. In this study, the intracellular metabolic profile of T. reesei RUT-C30 and A. niger N402 strains grown on glucose, lactose, carboxymethylcellulose (CMC), and steam-exploded sugarcane bagasse (SEB) as carbon sources for 48 h was analysed by proton nuclear magnetic resonance. The aim was to verify the changes in the primary metabolism triggered by these substrates and use transcriptomics data from the literature to better understand the dynamics of the observed alterations. Glucose and CMC induced higher fungal growth whereas fungi grown on lactose showed the lowest dry weight. Metabolic profile analysis revealed that mannitol, trehalose, glutamate, glutamine, and alanine were the most abundant metabolites in both fungi regardless of the carbon source. These metabolites are of particular interest for the mobilization of carbon and nitrogen, and stress tolerance inside the cell. Their concomitant presence indicates conserved mechanisms adopted by both fungi to assimilate carbon sources of different levels of recalcitrance. Moreover, the higher levels of galactose intermediates in T. reesei suggest its better adaptation in lactose, whereas glycolate and malate in CMC might indicate activation of the glyoxylate shunt. Glycerol and 4-aminobutyrate accumulated in A. niger grown on CMC and lactose, suggesting their relevant role in these carbon sources. In SEB, a lower quantity and diversity of metabolites were identified compared to the other carbon sources, and the metabolic changes and higher xylanase and pNPGase activities indicated a better utilization of bagasse by A. niger. Transcriptomic analysis supported the observed metabolic changes and pathways identified in this work. Taken together, we have advanced the knowledge about how fungal primary metabolism is affected by different carbon sources, and have drawn attention to metabolites still unexplored. These findings might ultimately be considered for developing more robust and efficient microbial factories.
Identification of core genes as potential biomarkers for predicting progression and prognosis in glioblastoma
Authors: Zeng Jianping , Hua Shushan , Liu Jing , Mungur Rajneesh , He Yongsheng , Feng Jiugeng 
Published: September 2022

Background: Glioblastoma is a common malignant neuroepithelial neoplasm with poor clinical outcomes and limited treatment options. It is extremely important to search and confirm diverse hub genes that are effective in the advance and prediction of glioblastoma.Methods: We analyzed GSE50161, GSE4290, and GSE68848, the three microarray datasets retrieved from the GEO database. GO function and KEGG pathway enrichment analyses for differentially expressed genes (DEGs) were performed using DAVID. The PPI network of the DEGs was analyzed using the Search Tool for the Retrieval of Interacting Genes database and visualized by Cytoscape software. Hub genes were identified through the PPI network and a robust rank aggregation method. The Cancer Genome Atlas (TCGA) and the Oncomine database were used to validate the hub genes. In addition, a survival curve analysis was conducted to verify the correlation between the expression of hub genes and patient prognosis. Human glioblastoma cells and normal cells were collected, and then RT-PCR, Western blot, and immunofluorescence were conducted to validate the expression of the NDC80 gene. A cell proliferation assay was used to detect the proliferation of glioma cells. The effects of NDC80 expression on migration and invasion of GBM cell lines were evaluated by conducting scratch and transwell assays.Results: A total of 716 DEGs were common to all three microarray datasets, which included 188 upregulated DEGs and 528 downregulated DEGs. Furthermore, we found that among the common DEGs, 10 hub genes showed a high degree of connectivity. The expression of the 10 hub genes in TCGA and the Oncomine database was significantly overexpressed in glioblastoma compared with normal genes. Additionally, the survival analysis showed that the patients with low expression of six genes (BIR5C, CDC20, NDC80, CDK1, TOP2A, and MELK) had a significantly favorable prognosis (p &lt; 0.01). We discovered that NDC80, which has been shown to be important in other cancers, also has an important role in malignant gliomas. The RT-PCR, Western blot, and immunofluorescence results showed that the expression level of NDC80 was significantly higher in human glioblastoma cells than in normal cells. Moreover, we identified that NDC80 increased the proliferation and invasion abilities of human glioblastoma cells.Conclusion: The six genes identified here may be utilized to form a panel of disease progression and predictive biomarkers of glioblastoma for clinical purposes. NDC80, one of the six genes, was discovered to have a potentially important role in GBM, a finding that needs to be further studied.
Identifying hub circadian rhythm biomarkers and immune cell infiltration in rheumatoid arthritis
Authors: Wen Pengfei , Ma Tao , Zhang Binfei , Hao Linjie , Wang Yakang , Guo Jianbin , Song Wei , Wang Jun , Zhang Yumin 
Published: September 2022

BackgroundRheumatoid arthritis (RA) is a chronic systemic autoimmune disease with symptoms characterized by typical circadian rhythmic changes. This study aimed to identify the hub circadian rhythm genes (CRGs) in RA and explore their association with immune cell infiltration and pathogenesis of RA.MethodsThe differentially expressed CRGs (DECRGs) between RA and normal control samples were screened from Datasets GSE12021 and GSE55235. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and Gene Set Enrichment Analysis were used to explore the potential functional mechanisms of DECRGs in RA. Weighted Gene Co-expression Network Analysis and Least Absolute Shrinkage and Selection Operator regression analysis were performed to identify hub CRGs of RA. CIBERSORT was conducted to compare the infiltration level of immune cells in RA and control synovial tissue and their relationship with hub genes. In addition, the diagnostic value of hub biomarkers was evaluated by the area under the receiver operator characteristic curve. Further, a nomogram prediction model was constructed and its significance for clinical decision-making was evaluated.ResultsThe green module was identified as the hub module associated with RA. Four hub CRGs (EGR1, FOSL2, GADD45B, and NFIL3) were identified and showed that they had the highest specificity and sensitivity for RA diagnosis, respectively. The expression levels and diagnostic values of these genes were externally validated in the dataset GSE55457. A nomogram prediction model based on the four hub CRGs was constructed and proved to have a certain clinical decision value. Additionally, the correlation analysis of immune cells with hub genes showed that all hub genes were significantly positively correlated with activated mast cells, resting memory CD4+ T cells, and monocytes. Whereas, all hub genes were negatively correlated with plasma cells, CD8+ T cells, and activated memory CD4+ T cells. Meanwhile, FOSL2 and GADD45B were negatively correlated with Tfh cells.ConclusionFour hub CRGs were identified and showed excellent diagnostic value for RA. These genes may be involved in the pathological process of RA by disrupting the rhythmic oscillations of cytokines through immune-related pathways and could be considered molecular targets for future chronotherapy against RA.
Systematic pattern analyses of Vδ2+ TCRs reveal that shared “public” Vδ2+ γδ T cell clones are a consequence of rearrangement bias and a higher expansion status
Authors: Deng Lihua , Harms Anna , Ravens Sarina , Prinz Immo , Tan Likai 
Published: September 2022

BackgroundVγ9Vδ2+T cells are a major innate T cell subset in human peripheral blood. Their Vδ2+VDJ-rearrangements are short and simple in the fetal thymus and gradually increase in diversity and CDR3 length along with development. So-called “public” versions of Vδ2+TCRs are shared among individuals of all ages. However, it is unclear whether such frequently occurring “public” Vγ9Vδ2+T cell clones are derived from the fetal thymus and whether they are fitter to proliferate and persist than infrequent “private” clones.MethodsShared “public” Vδ2+TCRs were identified from Vδ2+TCR-repertoires collected from 89 individuals, including newborns (cord blood), infants, and adults (peripheral blood). Distance matrices of Vδ2+CDR3 were generated by TCRdist3 and then embedded into a UMAP for visualizing the heterogeneity of Vδ2+TCRs.ResultsVδ2+CDR3 distance matrix embedded by UMAP revealed that the heterogeneity of Vδ2+TCRs is primarily determined by the J-usage and CDR3aa length, while age or publicity-specific motifs were not found. The most prevalent public Vδ2+TCRs showed germline-like rearrangement with low N-insertions. Age-related features were also identified. Public Vδ2+TRDJ1TCRs from cord blood showed higher N-insertions and longer CDR3 lengths. Synonymous codons resulting from VDJ rearrangement also contribute to the generation of public Vδ2+TCRs. Each public TCR was always produced by multiple different transcripts, even with different D gene usage, and the publicity of Vδ2+TCRs was positively associated with expansion status.ConclusionTo conclude, the heterogeneity of Vδ2+TCRs is mainly determined byTRDJ-usage and the length of CDR3aa sequences. Public Vδ2+TCRs result from germline-like rearrangement and synonymous codons, associated with a higher expansion status.
Exploring the risk factors for ischemic cerebrovascular disease in systemic lupus erythematosus: A single-center case-control study
Authors: Su Li , Qi Zhigang , Guan Shaochen , Wei Lian , Zhao Yi 
Published: September 2022

ObjectivesIschemic cerebrovascular disease (ICVD) is one of the most common and severe complications in systemic lupus erythematosus (SLE). We aim to explore the risk factors for ICVD in SLE and to assess their associated clinical characteristics.MethodsIn this study, 44 lupus patients with ICVD (ICVD-SLE) and 80 age- and sex-matched lupus patients without ICVD (non-ICVD-SLE) who were hospitalized in our center between 2014 and 2021 were enrolled. A comprehensive set of clinical and socio-demographic data was recorded. In the ICVD-SLE group, the modified Rankin score (mRS) at 90 days after the occurrence of ICVD, the brain MRI, and arterial ultrasonography findings were collected. Group comparisons were made with continuous variables using an independent t-test or the Mann–Whitney test, and with categorical variables using the chi-square test or Fisher exact test. Multivariate logistic regression analysis was performed to identify the risk factors for ICVD in SLE. Patients with ICVD-SLE were divided into three subgroups according to the gradations of intracranial arterial stenosis (ICAS). The subgroup comparisons were performed by one-way ANOVA test or Kruskal–Wallis test.ResultsOf the 44 patients with ICVD, 45% had a large-vessel ischemic stroke, 50% had a symptomatic lacunar stroke, and 9% had a transient ischemic attack. 2 (4.5%) had both large-vessel ischemic stroke and symptomatic lacunar stroke. Multivariate logistic regression analysis showed that cutaneous vasculitis (OR=7.36, 95% CI=2.11–25.65), anticardiolipin antibody (aCL) (OR=4.38, 95% CI=1.435–13.350), and lupus anticoagulant (LA) (OR=7.543,95% CI=1.789–31.808) were the risk factors, and hydroxychloroquine (HCQ) therapy (OR=0.198, 95% CI=0.078–0.502) was the protective factor, after controlling for confounders. During the analysis of the subgroups, no significant difference was observed between the patients in the group without internal carotid arterial occlusion (ICAS) and those with severe ICAS except for diagnostic delay. However, patients in the moderate ICAS group were older when SLE occurred (P&lt;0.01), had a longer diagnostic delay (P&lt;0.01), a lower percentage of hypocomplementemia (P=0.05) and steroids and HCQ therapy (P=0.01, P=0.05, respectively), a trend toward lower mRS score, but a higher incidence of carotid atherosclerotic plaque (P&lt;0.01), when compared with the other two subgroups.ConclusionCutaneous vasculitis and antiphospholipid antibodies (aPLs) are associated with an increased risk of ICVD, while HCQ therapy may provide protection against ICVD in SLE. The ICVD in younger lupus patients is associated with complement-mediated inflammation and poorer outcome, and require immunosuppressive therapy, whereas the ICVD in elderly patients are characterized by moderate ICAS and carotid atherosclerotic plaques.
Predictive mutation signature of immunotherapy benefits in NSCLC based on machine learning algorithms
Authors: Liu Zhichao , Lin Guo , Yan Zeping , Li Linduo , Wu Xingchen , Shi Jingrong , He Jianxing , Zhao Lei , Liang Hengrui , Wang Wei 
Published: September 2022

BackgroundDeveloping prediction tools for immunotherapy approaches is a clinically important and rapidly emerging field. The routinely used prediction biomarker is inaccurate and may not adequately utilize large amounts of medical data. Machine learning is a promising way to predict the benefit of immunotherapy from individual data by individuating the most important features from genomic data and clinical characteristics.MethodsMachine learning was applied to identify a list of candidate genes that may predict immunotherapy benefits using data from the published cohort of 853 patients with NSCLC. We used XGBoost to capture nonlinear relations among many mutation genes and ICI benefits. The value of the derived machine learning-based mutation signature (ML-signature) on immunotherapy efficacy was evaluated and compared with the tumor mutational burden (TMB) and other clinical characteristics. The predictive power of ML-signature was also evaluated in independent cohorts of patients with NSCLC treated with ICI.ResultsWe constructed the ML-signature based on 429 (training/validation = 8/2) patients who received immunotherapy and extracted 88 eligible predictive genes. Additionally, we conducted internal and external validation with the utility of the OAK+POPLAR dataset and independent cohorts, respectively. This ML-signature showed the enrichment in immune-related signaling pathways and compared to TMB, ML-signature was equipped with favorable predictive value and stratification.ConclusionPrevious studies proposed no predictive difference between original TMB and modified TMB, and original TMB contains some genes with no predictive value. To demonstrate that fewer genetic tests are sufficient to predict immunotherapy efficacy, we used machine learning to screen out gene panels, which are used to calculate TMB. Therefore, we obtained the 88-gene panel, which showed the favorable prediction performance and stratification effect compared to the original TMB.
Ocean acidification research in the Mediterranean Sea: Status, trends and next steps
Authors: Hassoun Abed El Rahman , Bantelman Ashley , Canu Donata , Comeau Steeve , Galdies Charles , Gattuso Jean-Pierre , Giani Michele , Grelaud Michaël , Hendriks Iris Eline , Ibello Valeria , Idrissi Mohammed , Krasakopoulou Evangelia , Shaltout Nayrah , Solidoro Cosimo , Swarzenski Peter W. , Ziveri Patrizia 
Published: September 2022

Ocean acidification (OA) is a serious consequence of climate change with complex organism-to-ecosystem effects that have been observed through field observations but are mainly derived from experimental studies. Although OA trends and the resulting biological impacts are likely exacerbated in the semi-enclosed and highly populated Mediterranean Sea, some fundamental knowledge gaps still exist. These gaps are at tributed to both the uneven capacity for OA research that exists between Mediterranean countries, as well as to the subtle and long-term biological, physical and chemical interactions that define OA impacts. In this paper, we systematically analyzed the different aspects of OA research in the Mediterranean region based on two sources: the United Nation’s International Atomic Energy Agency’s (IAEA) Ocean Acidification International Coordination Center (OA-ICC) database, and an extensive survey. Our analysis shows that 1) there is an uneven geographic capacity in OA research, and illustrates that both the Algero-Provencal and Ionian sub-basins are currently the least studied Mediterranean areas, 2) the carbonate system is still poorly quantified in coastal zones, and long-term time-series are still sparse across the Mediterranean Sea, which is a challenge for studying its variability and assessing coastal OA trends, 3) the most studied groups of organisms are autotrophs (algae, phanerogams, phytoplankton), mollusks, and corals, while microbes, small mollusks (mainly pteropods), and sponges are among the least studied, 4) there is an overall paucity in socio-economic, paleontological, and modeling studies in the Mediterranean Sea, and 5) in spite of general resource availability and the agreement for improved and coordinated OA governance, there is a lack of consistent OA policies in the Mediterranean Sea. In addition to highlighting the current status, trends and gaps of OA research, this work also provides recommendations, based on both our literature assessment and a survey that targeted the Mediterranean OA scientific community. In light of the ongoing 2021-2030 United Nations Decade of Ocean Science for Sustainable Development, this work might provide a guideline to close gaps of knowledge in the Mediterranean OA research.Systematic Review Registrationhttps://www.oceandecade.org/
Factors Affecting Selection of a Dialysis Modality in Elderly Patients With Chronic Kidney Disease: A Prospective Cohort Study in Korea
Authors: Cho Jang-Hee , Lim Jeong-Hoon , Park Yeongwoo , Jeon Yena , Kim Yon Su , Kang Shin-Wook , Yang Chul Woo , Kim Nam-Ho , Jung Hee-Yeon , Choi Ji-Young , Park Sun-Hee , Kim Chan-Duck , Kim Yong-Lim 
Published: September 2022

BackgroundWe investigated factors associated with the selection of a dialysis modality for elderly patients compared to younger patients.MethodsThis study included 2,514 incident dialysis patients from a Korean multicenter prospective cohort. Multivariate logistic regression analyses were performed with demographic, socioeconomic, and clinical data to analyze factors associated with the chosen dialysis modality. Differences in these factors were compared between the elderly (≥65 years) and younger (&lt;65 years) patients.ResultsOf the enrolled patients, 1,746 (69.5%) and 768 (30.6%) selected hemodialysis (HD) and peritoneal dialysis (PD), respectively. The percentage of PD was higher in younger patients than in elderly patients (37.1 vs. 16.9%, p &lt; 0.001). Multivariate analysis showed that planned dialysis (p &lt; 0.001), employment status (p &lt; 0.001), and independent economic status (p = 0.048) were independent factors for selecting PD, whereas peripheral vascular disease (p = 0.038) and tumor (p = 0.010) were factors for selecting HD in the younger group. In the elderly group, planned dialysis (p &lt; 0.001) and congestive heart failure (CHF; p = 0.002) were associated with choosing PD; however, tumor (p = 0.006) was associated with choosing HD. A two-way ANOVA showed that planned dialysis and CHF showed a significant interaction effect with age on modality selection.ConclusionsAs the age of patients with chronic kidney disease increased, HD was more frequently selected compared to PD. Dialysis planning and CHF interacted with age in selecting dialysis modalities in elderly patients. Elderly patients were less affected by socioeconomic status than younger patients.