bluuebunny/crossref_metadata_2025_split huggingface dataset:
Carbon quantum dots: An environmentally friendly and valued approach to sludge disposal
Authors: Rossi Bruno L. , Andrade Cláudia M. B. , Therézio Eralci M. , Ramos Romildo J. , Vasconcelos Leonardo G. , Terezo Ailton J. , De Siqueira Adriano B. 
Published: August 2022

Sewage sludge, produced daily and inherent to urban development, presents problems of disposal that are still challenging today. Its disposal still offers palliative solutions, where the final destination is generally in landfills or, restrictively, to use in agriculture. The synthesis of carbon quantum dots (CQDs) from sewage sludge is a better alternative to use the stock of organic material present in the sludge. The present work aims to produce Carbon quantum dots (CQDs) using principles of green chemistry and to use an alternative raw material intrinsic stock of carbon present in sewage sludge, making its final disposal more sustainable. The material obtained has a core structure mainly composed of sp2 carbon and nitrogen. The surface functional groups containing sulfur, nitrogen, and oxygen of CQDs were investigated using FTIR and TG/DSC coupled FTIR techniques. The CQDs showed a luminescence decay time equivalent to fluorescent compounds and with satisfying quantum yield since no passive/oxidizing agent or material purification process was used. The photoluminescence spectroscopy analysis showed that the CDQs excitation λmax was at 360 nm and caused a λmax emission at 437 nm (CQDsa) and 430 nm (CQDsb). The CQDs obtained showed sizes of 9.69 ± 2.64 nm (CQDsa) and 10.92 ± 2.69 nm (CQDsb). In vitro experiments demonstrated the uptake of CQDs by the endothelial cell line EAhy 926 and their nontoxicity. However, the production of CQDs can be used for the sustainable disposal of sewage sludge.
The MELD-XI score predicts 3-year mortality in patients with chronic heart failure
Authors: Lin Zebin , Liu Xia , Xiao Li , Li Yin , Qi Chenlu , Song Siqi , Zhao Yiping , Zou Lili 
Published: August 2022

ObjectivesThe relationship between the MELD-XI score, a modified version of the MELD score, and the long-term prognosis of hospitalized patients with chronic heart failure is unclear. The aim of this study was to determine the long-term prognostic relationship of MELD-XI score in patients with chronic heart failure.MethodsThis is a retrospective cohort study of patients with chronic heart failure who were initially hospitalized in the Second Affiliated Hospital of Chongqing Medical University from February 2017 to December 2017. The primary clinical outcome was all-cause mortality within 3 years. Cox regression and lasso regression were used to screen variables and build a prognostic model. Combined with the MELD-XI score, the final model was adjusted, and the predictive ability of the model was evaluated. Survival curves were estimated using the Kaplan–Meier method and compared by the log rank test.ResultsA total of 400 patients with chronic heart failure were included (median age 76 years, 51.5% female). During the 3-year follow-up period, there were 97 all-cause deaths, including 63 cardiac deaths. Six characteristic variables (NT-proBNP, BUN, RDW CV, Na+ and prealbumin) were selected by univariate Cox regression and lasso regression. Survival analysis results showed that elevated MELD-XI score at baseline predicted the risk of all-cause mortality at 3 years in patients (HR 3.19, 95% CI 2.11–4.82, P &lt; 0.001; HRadjusted 1.79, 95% CI 1.09–2.92, P = 0.020). Subgroup analysis showed that MELD-XI score still had prognostic value in the subgroup without chronic kidney disease (HR 3.30 95%CI 2.01–5.42 P &lt; 0.001; HRadjusted 1.88 95%CI 1.06–3.35 P = 0.032, P for interaction = 0.038).ConclusionsThis study proved that the MELD-XI score at admission was related to the poor prognosis of hospitalized patients with chronic heart failure within 3 years.
The Effects of Engineered Aeration on Atmospheric Methane Flux From a Chesapeake Bay Tidal Tributary
Authors: Lapham Laura L. , Hobbs Edward A. , Testa Jeremy M. , Heyes Andrew , Forsyth Melinda K. , Hodgkins Casey , Szewczyk Curtis , Harris Lora A. 
Published: August 2022

Engineered aeration is one solution for increasing oxygen concentrations in highly eutrophic estuaries that undergo seasonal hypoxia. Although there are various designs for engineered aeration, all approaches involve either destratification of the water column or direct injection of oxygen or air through fine bubble diffusion. To date, the effect of either approach on estuarine methane dynamics remains unknown. Here we tested the hypotheses that 1) bubble aeration will strip the water of methane and enhance the air-water methane flux to the atmosphere and 2) the addition of oxygen to the water column will enhance aerobic methane oxidation in the water column and potentially offset the air-water methane flux. These hypotheses were tested in Rock Creek, Maryland, a shallow-water sub-estuary to the Chesapeake Bay, using controlled, ecosystem-scale deoxygenation experiments where the water column and sediments were sampled in mid-summer, when aerators were ON, and then 1, 3, 7, and 13 days after the aerators were turned OFF. Experiments were performed under two system designs, large bubble and fine bubble approaches, using the same observational approach that combined discrete water sampling, long term water samplers (OsmoSamplers) and sediment porewater profiles. Regardless of aeration status, methane concentrations reached as high as 1,500 nmol L−1 in the water column during the experiments and remained near 1,000 nmol L−1 through the summer and into the fall. Since these concentrations are above atmospheric equilibrium of 3 nmol L−1, these data establish the sub-estuary as a source of methane to the atmosphere, with a maximum atmospheric flux as high as 1,500 µmol m−2 d−1, which is comparable to fluxes estimated for other estuaries. Air-water methane fluxes were higher when the aerators were ON, over short time frames, supporting the hypothesis that aeration enhanced the atmospheric methane flux. The fine-bubble approach showed lower air-water methane fluxes compared to the larger bubble, destratification system. We found that the primary source of the methane was the sediments, however, in situ methane production or an upstream methane source could not be ruled out. Overall, our measurements of methane concentrations were consistently high in all times and locations, supporting consistent methane flux to the atmosphere.
An inflammation-related signature could predict the prognosis of patients with kidney renal clear cell carcinoma
Authors: Yu Qingxin , Zhang Facai , Feng Dechao , Li Dengxiong , Xia Yuhui , Gan Mei-Fu 
Published: August 2022

Background: Kidney renal clear cell carcinoma (KIRC) is an inflammation-related carcinoma, and inflammation has been recognized as an important factor in inducing carcinogenesis. To further explore the role of inflammation in KIRC, we developed an inflammation-related signature and verified its correlation with the tumor micro-environment.Methods: After the differential inflammation-related prognostic genes were screened by Lasso regression, the inflammation-related signature (IRS) was constructed based on the risk score of multivariate Cox regression. Then, the prognostic value of the IRS was evaluated by Kaplan-Meier analysis, receiver operating characteristic (ROC) curve analysis and multivariate Cox regression. Gene set variation analysis (GSVA) was applied to screen out enriched signaling pathways. Infiltrated immune cells, tumor mutational burden (TMB) and immune checkpoints were explored by CIBERSORTx and maftool.Results: Four genes (TIMP1, PLAUR, CCL22, and IL15RA) were used to construct the IRS in patients with KIRC. Kaplan-Meier analysis and multivariate Cox regression identified that the IRS could independently predict the prognosis of patients with KIRC in the training and validation groups. The diagnostic value of the nomogram increased from 0.811 to 0.845 after adding the IRS to the multiparameter ROC analysis. The GSVA results indicated that IRS was closely related to primary immunodeficiency and antigen processing and presentation. The immune checkpoint LAG3 was highly expressed in patients with high-risk score (p &lt; 0.05), while CD274 (PD-L1) and HAVCR2 were highly expressed in patients with low-risk score (p &lt; 0.001). There was a significant positive correlation between the high-risk score group and CD8+ T, activated CD4+ memory T, gamma and delta regulatory T and M0 macrophage cells, while the low-risk score group was negatively associated with B memory, plasma, resting CD4+ memory T, activated NK, M1 macrophages and resting mast cells.Conclusion: We found that the IRS might serve as a biomarker to predict the survival of KIRC. Moreover, patients with high or low-risk score might be sensitive to immune drugs at different immune checkpoints.
The Usefulness of a Targeted Next Generation Sequencing Gene Panel in Providing Molecular Diagnosis to Patients With a Broad Spectrum of Neurodevelopmental Disorders
Authors: Mellone Simona , Puricelli Chiara , Vurchio Denise , Ronzani Sara , Favini Simone , Maruzzi Arianna , Peruzzi Cinzia , Papa Amanda , Spano Alice , Sirchia Fabio , Mandrile Giorgia , Pelle Alessandra , Rasmini Paolo , Vercellino Fabiana , Zonta Andrea , Rabbone Ivana , Dianzani Umberto , Viri Maurizio , Giordano Mara 
Published: August 2022

Background: Neurodevelopmental disorders comprise a clinically and genetically heterogeneous group of conditions that affect 2%–5% of children and represents a public health challenge due to complexity of the etiology. Only few patients with unexplained syndromic and non-syndromic NDDs receive a diagnosis through first-tier genetic tests as array-CGH and the search for FMR1 CGG expansion. The aim of this study was to evaluate the clinical performance of a targeted next-generation sequencing (NGS) gene panel as a second-tier test in a group of undiagnosed patients with NDDs.Method: A 221-gene next-generation sequencing custom panel was designed and used to analyze a cohort of 338 patients with a broad spectrum of NDDs (202 males and 136 females) including Intellectual Disability (ID), Autism Spectrum Disorders (ASD), Epilepsy, language and motor disorders.Results: A molecular diagnosis was established in 71 patients (21%) and a de novo origin was present in 38 (64.4%) of the available trios. The diagnostic yield was significantly higher in females than in males (29.4% vs. 15.3%; p = 0.0019) in particular in ASD (36.8% vs. 7.6%; p = 0.0026) and Epilepsy (38.9% vs. 14.4% p = 0.001). The most involved genes were SLC2A1, SCN1A, ANKRD11, ATP1A2, CACNA1A, FOXP1, and GNAS altered in more than two patients and accounting for the 19.7% of the diagnosis.Conclusion: Our findings showed that this NGS panel represents a powerful and affordable clinical tool, significantly increasing the diagnostic yield in patients with different form of NDDs in a cost- and time-effective manner without the need of large investments in data storage and bioinformatic analysis.
Identification of Ferroptosis-Related Molecular Clusters and Immune Characterization in Autism Spectrum Disorder
Authors: Liu Lichun , Lai Yongxing , Zhan Zhidong , Fu Qingxian , Jiang Yuelian 
Published: August 2022

Introduction: Autism spectrum disorder (ASD) is a neurodevelopmental disorder with clinical presentation and prognostic heterogeneity. Ferroptosis is a regulated non-apoptotic cell death program implicated in the occurrence and progression of various diseases. Therefore, we aimed to explore ferroptosis-related molecular subtypes in ASD and further illustrate the potential mechanism.Methods: A total of 201 normal samples and 293 ASD samples were obtained from the Gene Expression Omnibus (GEO) database. We used the unsupervised clustering analysis to identify the molecular subtypes based on ferroptosis-related genes (FRGs) and evaluate the immune characteristics between ferroptosis subtypes. Ferroptosis signatures were identified using the least absolute shrinkage and selection operator regression (LASSO) and recursive feature elimination for support vector machines (SVM-RFE) machine learning algorithms. The ferroptosis scores based on seven selected genes were constructed to evaluate the ferroptosis characteristics of ASD.Results: We identified 16 differentially expressed FRGs in ASD children compared with controls. Two distinct molecular clusters associated with ferroptosis were identified in ASD. Analysis of immune infiltration revealed immune heterogeneity between the two clusters. Cluster2, characterized by a higher immune score and a larger number of infiltrated immune cells, exhibited a stronger immune response and was markedly enriched in immune response-related signaling pathways. Additionally, the ferroptosis scores model was capable of predicting ASD subtypes and immunity. Higher levels of ferroptosis scores were associated with immune activation, as seen in Cluster2. Lower ferroptosis scores were accompanied by relative immune downregulation, as seen in Cluster1.Conclusion: Our study systematically elucidated the intricate correlation between ferroptosis and ASD and provided a promising ferroptosis score model to predict the molecular clusters and immune infiltration cell profiles of children with ASD.
Integrative analysis of a necroptosis-related gene signature of clinical value and heterogeneity in diffuse large B cell lymphoma
Authors: Pan Yu-Biao , Wang Wei , Cai Hong-Kai , Zhang Jia , Teng Ya , Xue Jiji , Zhu Min , Luo Wen-Da 
Published: August 2022

Background: Diffuse large B-cell lymphoma (DLBCL), which is considered to be the most common subtype of lymphoma, is an aggressive tumor. Necroptosis, a novel type of programmed cell death, plays a bidirectional role in tumors and participates in the tumor microenvironment to influence tumor development. Targeting necroptosis is an intriguing direction, whereas its role in DLBCL needs to be further discussed.Methods: We obtained 17 DLBCL-associated necroptosis-related genes by univariate cox regression screening. We clustered in GSE31312 depending on their expressions of these 17 genes and analyzed the differences in clinical characteristics between different clusters. To investigate the differences in prognosis across distinct clusters, the Kaplan-Meier method was utilized. The variations in the tumor immune microenvironment (TME) between distinct necroptosis-related clusters were investigated via “ESTIMATE”, “Cibersort” and single-sample geneset enrichment analysis (ssGSEA). Finally, we constructed a 6-gene prognostic model by lasso-cox regression and subsequently integrated clinical features to construct a prognostic nomogram.Results: Our analysis indicated stable but distinct mechanism of action of necroptosis in DLBCL. Based on necroptosis-related genes and cluster-associated genes, we identified three groups of patients with significant differences in prognosis, TME, and chemotherapy drug sensitivity. Analysis of immune infiltration in the TME showed that cluster 1, which displayed the best prognosis, was significantly infiltrated by natural killer T cells, dendritic cells, CD8+ T cells, and M1 macrophages. Cluster 3 presented M2 macrophage infiltration and the worst prognosis. Importantly, the prognostic model successfully differentiated high-risk from low-risk patients, and could forecast the survival of DLBCL patients. And the constructed nomogram demonstrated a remarkable capacity to forecast the survival time of DLBCL patients after incorporating predictive clinical characteristics.Conclusion: The different patterns of necroptosis explain its role in regulating the immune microenvironment of DLBCL and the response to R-CHOP treatment. Systematic assessment of necroptosis patterns in patients with DLBCL will help us understand the characteristics of tumor microenvironment cell infiltration and aid in the development of tailored therapy regimens.
Identification and validation of differentially expressed chromatin regulators for diagnosis of aortic dissection using integrated bioinformatics analysis and machine-learning algorithms
Authors: Liu Chunjiang , Zhou Yufei , Zhao Di , Yu Luchen , Zhou Yue , Xu Miaojun , Tang Liming 
Published: August 2022

Background: Aortic dissection (AD) is a life-threatening disease. Chromatin regulators (CRs) are indispensable epigenetic regulators. We aimed to identify differentially expressed chromatin regulators (DECRs) for AD diagnosis.Methods: We downloaded the GSE52093 and GSE190635 datasets from the Gene Expression Omnibus database. Following the merging and processing of datasets, bioinformatics analysis was applied to select candidate DECRs for AD diagnosis: CRs exertion; DECR identification using the “Limma” package; analyses of enrichment of function and signaling pathways; construction of protein–protein interaction (PPI) networks; application of machine-learning algorithms; evaluation of receiver operating characteristic (ROC) curves. GSE98770 served as the validation dataset to filter DECRs. Moreover, we collected peripheral-blood samples to further validate expression of DECRs by real-time reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Finally, a nomogram was built for clinical use.Results: A total of 841 CRs were extracted from the merged dataset. Analyses of functional enrichment of 23 DECRs identified using Limma showed that DECRs were enriched mainly in epigenetic-regulation processes. From the PPI network, 17 DECRs were selected as node DECRs. After machine-learning calculations, eight DECRs were chosen from the intersection of 13 DECRs identified using support vector machine recursive feature elimination (SVM-RFE) and the top-10 DECRs selected using random forest. DECR expression between the control group and AD group were considerably different. Moreover, the area under the ROC curve (AUC) of each DECR was &gt;0.75, and four DECRs (tumor protein 53 (TP53), chromobox protein homolog 7 (CBX7), Janus kinase 2 (JAK2) and cyclin-dependent kinase 5 (CDK5)) were selected as candidate biomarkers after validation using the external dataset and clinical samples. Furthermore, a nomogram with robust diagnostic value was established (AUC = 0.960).Conclusion: TP53, CBX7, JAK2, and CDK5 might serve as diagnostic DECRs for AD diagnosis. These DECRs were enriched predominantly in regulating epigenetic processes.
Aging-based molecular classification and score system in ccRCC uncovers distinct prognosis, tumor immunogenicity, and treatment sensitivity
Authors: Zhu Maoshu , Huang Chaoqun , Wu Xinhong , Gu Ying , Hu Xiaoxu , Ma Dongna , Zhong Weimin 
Published: August 2022

ObjectiveAging is a complex biological process and a major risk factor for cancer development. This study was conducted to develop a novel aging-based molecular classification and score system in clear cell renal cell carcinoma (ccRCC).MethodsIntegrative analysis of aging-associated genes was performed among ccRCC patients in the TCGA and E-MTAB-1980 cohorts. In accordance with the transcriptional expression matrix of 173 prognostic aging-associated genes, aging phenotypes were clustered with the consensus clustering approach. The agingScore was generated to quantify aging phenotypes with principal component analysis. Tumor-infiltrating immune cells and the cancer immunity cycle were quantified with the ssGSEA approach. Immunotherapy response was estimated through the TIDE algorithm, and a series of tumor immunogenicity indicators were computed. Drug sensitivity analysis was separately conducted based on the GDSC, CTRP, and PRISM analyses.ResultsThree aging phenotypes were established for ccRCC, with diverse prognosis, clinical features, immune cell infiltration, tumor immunogenicity, immunotherapeutic response, and sensitivity to targeted drugs. The agingScore was developed, which enabled to reliably and independently predict ccRCC prognosis. Low agingScore patients presented more undesirable survival outcomes. Several small molecular compounds and three therapeutic targets, namely, CYP11A1, SAA1, and GRIK4, were determined for the low agingScore patients. Additionally, the high agingScore patients were more likely to respond to immunotherapy.ConclusionOverall, our findings introduced an aging-based molecular classification and agingScore system into the risk stratification and treatment decision-making in ccRCC.
Prediction of prognosis, immunogenicity and efficacy of immunotherapy based on glutamine metabolism in lung adenocarcinoma
Authors: Liu Jichang , Shen Hongchang , Gu Wenchao , Zheng Haotian , Wang Yadong , Ma Guoyuan , Du Jiajun 
Published: August 2022

BackgroundGlutamine (Gln) metabolism has been reported to play an essential role in cancer. However, a comprehensive analysis of its role in lung adenocarcinoma is still unavailable. This study established a novel system of quantification of Gln metabolism to predict the prognosis and immunotherapy efficacy in lung cancer. Further, the Gln metabolism in tumor microenvironment (TME) was characterized and the Gln metabolism-related genes were identified for targeted therapy.MethodsWe comprehensively evaluated the patterns of Gln metabolism in 513 patients diagnosed with lung adenocarcinoma (LUAD) based on 73 Gln metabolism-related genes. Based on differentially expressed genes (DEGs), a risk model was constructed using Cox regression and Lasso regression analysis. The prognostic efficacy of the model was validated using an individual LUAD cohort form Shandong Provincial Hospital, an integrated LUAD cohort from GEO and pan-cancer cohorts from TCGA databases. Five independent immunotherapy cohorts were used to validate the model performance in predicting immunotherapy efficacy. Next, a series of single-cell sequencing analyses were used to characterize Gln metabolism in TME. Finally, single-cell sequencing analysis, transcriptome sequencing, and a series of in vitro experiments were used to explore the role of EPHB2 in LUAD.ResultsPatients with LUAD were eventually divided into low- and high-risk groups. Patients in low-risk group were characterized by low levels of Gln metabolism, survival advantage, “hot” immune phenotype and benefit from immunotherapy. Compared with other cells, tumor cells in TME exhibited the most active Gln metabolism. Among immune cells, tumor-infiltrating T cells exhibited the most active levels of Gln metabolism, especially CD8 T cell exhaustion and Treg suppression. EPHB2, a key gene in the model, was shown to promote LUAD cell proliferation, invasion and migration, and regulated the Gln metabolic pathway. Finally, we found that EPHB2 was highly expressed in macrophages, especially M2 macrophages. It may be involved in the M2 polarization of macrophages and mediate the negative regulation of M2 macrophages in NK cells.ConclusionThis study revealed that the Gln metabolism-based model played a significant role in predicting prognosis and immunotherapy efficacy in lung cancer. We further characterized the Gln metabolism of TME and investigated the Gln metabolism-related gene EPHB2 to provide a theoretical framework for anti-tumor strategy targeting Gln metabolism.