bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multiscale Shear Properties and Flow Performance of Milled Woody Biomass
Authors: Klinger Jordan , Saha Nepu , Bhattacharjee Tiasha , Carilli Susan , Jin Wencheng , Xia Yidong , Daniel Richard , Burns Carolyn , Ajayi Oyelayo , Cheng Ziwei , Navar Ricardo , Semelsberger Troy 
Published: July 2022

One dominant challenge facing the development of biorefineries is achieving consistent system throughput with highly variant biomass feedstock quality and handling performance. Current handling unit operations are adapted from other sectors (primarily agriculture), where some simplifying assumptions about granular mechanics and flow performance do not translate well to a highly compressible and anisotropic material with nonlinear time- and stress-dependent properties. This work explores the shear and frictional properties of loblolly pine at multiple experimental test apparatus and particle scales to elucidate a property window that defines the shear behavior over a range of material attributes (particle size, size distribution, moisture content, etc.). In general, it was observed that the bulk internal friction and apparent cohesion depend strongly on both the stress state of the sample in granular shear testers and the overall particle size and distribution span. For equipment designed to characterize the quasi-static shear stress failure of bulk materials ranging from 50 to 1,000 ml in test volume, similar test results were observed for finely milled particles (50% passing size of 1.4 mm) with a narrow size distribution (span between 10 and 90% passing size of 0.9 mm), while stress chaining and over-torque issues persisted for the bench-scale test apparatus for larger particle sizes or widely dispersed sample sizes. Measurement of the anisotropic particle–particle friction ranged from coefficients of approximately 0.20 to 0.45 and resulted in significantly higher and more variable friction measurements for larger particle sizes and in perpendicular alignment orientations. To supplement these laboratory-scale properties, this work explores the flow of loblolly pine and Douglas fir through a pilot-scale wedge-shaped hopper and a screw feeder. For the gravity-driven hopper flow, the critical arching distance and mass discharge rate ranged from approximately 10 to 30 mm and 2 to 16 tons/hour, respectively, for both materials, where the arching distance depends strongly on the overall particle size and depends less on the hopper inclination angle. Comparatively, the auger feeder was found to be much more impacted by the size of the particles, where smaller particles had a more consistent and stable flow while consuming less power.
Study on Advanced Nitrogen Removal and Microbial Community Structure of Traditional Chinese Medicine Wastewater by a Novel System Coupling Anaerobic Sequencing Batch Reactor and Modified Sequencing Batch Biofilm Reactor
Authors: Wang Kai , Jiang Jinfeng , Ma Liang , Zheng Liwen , Zhang Guangyuan , Wu Daoji 
Published: July 2022

To improve the efficiency of nitrogen removal from pharmaceutical wastewater, wastewater from traditional Chinese medicine was treated in an anaerobic sequencing batch reactor (ASBR) combined with a modified sequencing batch biofilm reactor (SBBR). The chemical oxygen demand (COD) and total nitrogen (TN) contents were 3,750 ± 50 mg/L and 210 ± 10 mg/L, respectively. After 99 days of start-up and domestication, the COD, NH4+-N, and TN contents in the effluent were 230 ± 10 mg/L, 1 ± 0.5 mg/L, and 5 ± 3 mg/L, respectively, and the removal efficiencies reached more than 93.5, 99, and 96%, respectively. Among these results, the COD removal efficiency in traditional Chinese medicine wastewater with an ASBR reached more than 85%, and the effluent and raw water were mixed to adjust the C/N ratio in the SBBR influent. The initial operation mode of the improved SBBR was anaerobic–aerobic–anoxic. When the C/N ratio in the influent was adjusted to 5, the simultaneous nitrification and denitrification (SND) in the aerobic section was gradually enhanced, and the endogenous denitrification (ED) in the anoxic section gradually decreased. In conclusion, deep denitrification of the system was achieved only through SND, and the running time of the cycle was shortened from the initial 24 to 4.6 h. High-throughput sequencing analysis showed that the relative abundances of Bacteroidetes and Proteobacteria in the system were 39.69 and 37.34%, respectively. The content of Firmicutes with denitrification in the system was also high, accounting for 5.17%. At the genus level, the bacteria with denitrification functions in the system were mainly Thauera and unidentified_Sphingobacteriales, accounting for 5.67 and 1.66% of the system, respectively. In addition, there was heterotrophic nitrification–aerobic denitrification (HN-AD) activated in the system, including Denitratisoma, Paracoccus, and Pseudomonas. The total relative abundance of these bacteria was 0.612%. Their existence may be one of the reasons for the good effect of SND in this system.
Microscopic observation of a liquid-liquid-(semi)solid phase in polluted PM2.5
Authors: Gaikwad Sanjit , Jeong Rani , Kim Dohyun , Lee Kwangyul , Jang Kyoung-Soon , Kim Changhyuk , Song Mijung 
Published: July 2022

Atmospheric aerosol particles are complex mixtures having various physicochemical properties. To predict the role and characteristics of such complex aerosol particles in air pollution and related atmospheric chemistry, our knowledge of the number and types of phases in complex aerosol particles should be improved. However, most studies on the phase behavior of aerosol particles have been conducted in the laboratory and have not used real-world aerosol particles. In this study, using a combination of optical microscopy and poke-and-flow technique, we investigated the number and types of phases of actual aerosol particles of particulate matter &lt; 2.5 µm (PM2.5) collected on heavily polluted days in Seosan, South Korea in winter 2020–2021. From the microscopic observations at 293 K, it showed that the PM2.5particles exist in a single liquid phase at relative humidity (RH) &gt;∼85%, a liquid-liquid phase at ∼70% &lt; RH &lt;∼85%, a liquid-liquid-(semi)solid phase at ∼30% &lt; RH &lt;∼70%, and a (semi)solid phase at RH &lt;∼30% upon dehydration. This reveals that three phases of atmospheric aerosol particles coexisting as liquid-liquid and liquid-liquid-(semi)solid would be the most common phases in the atmosphere considering ambient RH ranges. These observations provide fundamental properties necessary for improved predictions of air quality and aerosol chemistry such as reactive uptake of N2O5, size distributions, and mass concentrations of aerosol particles.
Construction of a Novel Prognostic Signature in Lung Adenocarcinoma Based on Necroptosis-Related lncRNAs
Authors: Diao Xiayao , Guo Chao , Li Shanqing 
Published: July 2022

Background: Long non-coding RNAs (lncRNAs) are drawing increasing attention as promising predictors of prognosis for lung adenocarcinoma (LUAD) patients. Necroptosis, a novel regulated mechanism of necrotic cell death, plays an important role in the biological process of cancer. The aim of this study was to identify the necroptosis-related lncRNAs (NRLRs) in a LUAD cohort and establish a necroptosis-related lncRNA signature (NRLSig) to stratify LUAD patients.Methods: NRLRs were identified in LUAD patients from The Cancer Genome Atlas (TCGA) database using Pearson correlation analysis between necroptosis-related genes and lncRNAs. Then the NRLSig was identified using univariate Cox regression analysis and LASSO regression analysis. Assessments of the signature were performed based on survival analysis, receiver operating characteristic (ROC) curve analysis and clustering analysis. Next, a nomogram containing the NRLSig and clinical information was developed through univariate and multivariate Cox regression analysis. Further, functional enrichment analysis of the selected lncRNAs in NRLSig and the association between NRLSig and the immune infiltration were also evaluated.Results: A 4-lncRNA signature, incorporating LINC00941, AP001453.2, AC026368.1, and AC236972.3, was identified to predict overall survival (OS) and stratify LUAD patients into different groups. Survival analysis, ROC curve analysis and clustering analysis showed good performance in the prognostic prediction of the lncRNA signature. Then, a nomogram containing the NRLSig was developed and showed satisfactory predictive accuracy, calibration and clinical usefulness. The co-expressed genes of selected NRLRs were enriched in several biological functions and signaling pathways. Finally, differences in the abundance of immune cells were investigated among the high-risk group and low-risk group divided by the NRLSig.Conclusion: The proposed NRLSig may provide promising therapeutic targets or prognostic predictors for LUAD patients.
N6-methyladenosine RNA methylation regulator-related alternative splicing gene signature as prognostic predictor and in immune microenvironment characterization of patients with low-grade glioma
Authors: Maimaiti Aierpati , Tuersunniyazi Abudireheman , Meng Xianghong , Pei Yinan , Ji Wenyu , Feng Zhaohai , Jiang Lei , Wang Zengliang , Kasimu Maimaitijiang , Wang Yongxin , Shi Xin 
Published: July 2022

Background: N6-methyladenosine (m6A) RNA methylation is an important epigenetic modification affecting alternative splicing (AS) patterns of genes to regulate gene expression. AS drives protein diversity and its imbalance may be an important factor in tumorigenesis. However, the clinical significance of m6A RNA methylation regulator-related AS in the tumor microenvironment has not been investigated in low-grade glioma (LGG).Methods: We used 12 m6A methylation modulatory genes (WTAP, FTO, HNRNPC, YTHDF2, YTHDF1, YTHDC2, ALKBH5, YTHDC1, ZC3H13, RBM15, METTL14, and METTL3) from The Cancer Genome Atlas (TCGA) database as well as the TCGA-LGG (n = 502) dataset of AS events and transcriptome data. These data were downloaded and subjected to machine learning, bioinformatics, and statistical analyses, including gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Univariate Cox, the Least Absolute Shrinkage and Selection Operator (LASSO), and multivariable Cox regression were used to develop prognostic characteristics. Prognostic values were validated using Kaplan-Maier survival analysis, proportional risk models, ROC curves, and nomograms. The ESTIMATE package, TIMER database, CIBERSORT method, and ssGSEA algorithm in the R package were utilized to explore the role of the immune microenvironment in LGG. Lastly, an AS-splicing factor (SF) regulatory network was examined in the case of considering the role of SFs in regulating AS events.Results: An aggregate of 3,272 m6A regulator-related AS events in patients with LGG were screened using six machine learning algorithms. We developed eight AS prognostic characteristics based on splice subtypes, which showed an excellent prognostic prediction performance. Furthermore, quantitative prognostic nomograms were developed and showed strong validity in prognostic prediction. In addition, prognostic signatures were substantially associated with tumor immune microenvironment diversity, ICB-related genes, and infiltration status of immune cell subtypes. Specifically, UGP2 has better promise as a prognostic factor for LGG. Finally, splicing regulatory networks revealed the potential functions of SFs.Conclusion: The present research offers a novel perspective on the role of AS in m6A methylation. We reveal that m6A methylation regulator-related AS events can mediate tumor progression through the immune-microenvironment, which could serve as a viable biological marker for clinical stratification of patients with LGG so as to optimize treatment regimens.
Precise, Genotype-First Breast Cancer Prevention: Experience With Transferring Monogenic Findings From a Population Biobank to the Clinical Setting
Authors: Jürgens Hannes , Roht Laura , Leitsalu Liis , Nõukas Margit , Palover Marili , Nikopensius Tiit , Reigo Anu , Kals Mart , Kallak Kersti , Kütner Riina , Budrikas Kai , Kuusk Saskia , Valvere Vahur , Laidre Piret , Toome Kadri , Rekker Kadri , Tooming Mikk , Ülle Murumets  , Kahre Tiina , Kruuv-Käo Krista , Õunap Katrin , Padrik Peeter , Metspalu Andres , Esko Tõnu , Fischer Krista , Tõnisson Neeme 
Published: July 2022

Although hereditary breast cancer screening and management are well accepted and established in clinical settings, these efforts result in the detection of only a fraction of genetic predisposition at the population level. Here, we describe our experience from a national pilot study (2018–2021) in which 180 female participants of Estonian biobank (of &gt;150,000 participants in total) were re-contacted to discuss personalized clinical prevention measures based on their genetic predisposition defined by 11 breast cancer–related genes. Our results show that genetic risk variants are relatively common in the average-risk Estonian population. Seventy-five percent of breast cancer cases in at-risk subjects occurred before the age of 50 years. Only one-third of subjects would have been eligible for clinical screening according to the current criteria. The participants perceived the receipt of genetic risk information as valuable. Fluent cooperation of project teams supported by state-of-art data management, quality control, and secure transfer can enable the integration of research results to everyday medical practice in a highly efficient, timely, and well-accepted manner. The positive experience in this genotype-first breast cancer study confirms the value of using existing basic genomic data from population biobanks for precise prevention.
Association Between the Individual and Combined Effects of the GSTM1 and GSTT1 Polymorphisms and Risk of Leukemia: A Meta-Analysis
Authors: Hu Ting , Zhou Guozhong , Li Wenjin 
Published: July 2022

Background: Fourteen meta-analyses reported the individual effects of the GSTM1 and GSTT1 polymorphisms on leukemia risk. However, over 40 studies were not included in previously published meta-analyses. Moreover, one key aspect was that previous meta-analyses did not conduct the false-positive test on the aforementioned issues. Furthermore, previous meta-analyses did not observe the combined effects of GSTM1 present/null and GSTT1 present/null polymorphism with leukemia risk. Therefore, we conducted the current study to further analyze these associations.Objectives: This study aimed to investigate the association between the individual and combined effects of the GSTM1 present/null and GSTT1 present/null polymorphisms and the risk of leukemia.Methods: A meta-analysis was performed applying Meta-analyses of Observational Studies in Epidemiology (MOOSE) guidelines. Moreover, false-positive report probability (FPRP) and Bayesian false discovery probability (BFDP) were applied to investigate the false-positive results.Results: The individual GSTM1 and GSTT1 null genotypes and combined effects of the two genes were associated with a significantly increased leukemia risk in overall and several subgroup analyses, such as Asians, Caucasians, and so on. Then, further analysis was conducted using FPRP and BFDP. Significant associations were considered as “positive” results on the GSTM1 null genotype with leukemia risk in overall populations (FPRP &lt; 0.001 and BFDP = 0.006), Asians (FPRP &lt; 0.001 and BFDP &lt; 0.001), and East Asian population (FPRP &lt; 0.001 and BFDP = 0.002). For the GSTT1 null genotype, significant associations were regarded “positive” results in overall populations, acute myeloid leukemia (AML), Asians, and East Asian population. For the combined effects of the GSTM1 and GSTT1 polymorphisms, significant associations were also considered “positive” results in the overall analysis of Asians, Indians, and East Asian population.Conclusion: This study strongly indicates that the individual GSTM1 and GSTT1 null genotypes and combined effects of the two genes are associated with increased leukemia risk in Asians, especially in the East Asian population; the GSTT1 null genotype is associated with increased AML risk; the combined effects of the two genes are associated with increased leukemia risk in Indians.
Association of SLC11A1 Polymorphisms With Tuberculosis Susceptibility in the Chinese Han Population
Authors: Hu Baoping , Wang Yuhe , Wang Zhongtao , He Xue , Wang Li , Yuan Dongya , He Yongjun , Jin Tianbo , He Shumei 
Published: July 2022

Tuberculosis (TB) is an important health issue in the world. Although the relation of SLC11A1 polymorphisms with TB risk has been extensively studied, it has not been reported in the northwest Chinese Han population. Therefore, this study aimed to investigate the relationships between five polymorphisms in or near the SLC11A1 gene and susceptibility to TB. The Agena MassARRAY platform was conducted for genotyping from 510 TB patients and 508 healthy controls. Odds ratios (ORs) and 95% confidence intervals (CIs) were analyzed through logistic regression adjustment age and gender to assess the relationships between polymorphisms and TB risk. Our results identified that rs7608307 was related to increased TB risk in males (CT vs. CC: OR = 1.69, 95%CI: 1.12–2.56, p = 0.013; CT-TT vs. CC: OR = 1.61, 95%CI: 1.08–2.41, p = 0.020) and age ≤41 group (CT vs. CC: OR = 1.66, 95%CI: 1.04–2.65, p = 0.035), respectively. The SNP rs13062 was associated with the TB risk both in males (p = 0.012) and age &gt;41 group (p = 0.021). In addition, we observed that the CC genotype of rs4674301 was correlated with increased TB risk in females (p = 0.043). Our results demonstrated the relationships between polymorphisms (rs7608307, rs4674301, and rs13062) in or near the SLC11A1 gene and age- and sex-specific TB risk in the northwest Chinese Han population.
Ferroptosis-Related Hub Genes in Hepatocellular Carcinoma: Prognostic Signature, Immune-Related, and Drug Resistance Analysis
Authors: Wang Wei , Pan Fan , Lin Xinrong , Yuan Jiakai , Tao Chunyu , Wang Rui 
Published: July 2022

Background: Hepatocellular carcinoma (HCC) is the most prevalent type of primary liver cancer with a high fatality rate and dismal prognosis because of frequent recurrence and lack of efficient therapies. Ferroptosis is a recently recognized iron-dependent cell death distinct from necroptosis and apoptosis. The relationship between ferroptosis-related hub gene expression and prognosis in HCC remains to be further elucidated.Methods: Ferroptosis-related genes from the FerrDb database and the mRNA sequencing data and clinical information of HCC patients were obtained from The Cancer Genome Atlas (TCGA) database. The least absolute shrinkage and selection operator (LASSO) Cox regression was applied to identify a prognostic signature consisting of five ferroptosis-related hub genes in the TCGA cohort. The International Cancer Genome Consortium (ICGC) database was utilized to validate the reliability of the signature. Functional enrichment and immune-related analysis, including single-sample gene set enrichment analysis (ssGSEA), immune checkpoints, TIP-related genes, tumor stemness, and m6A-related genes, were performed to analyze the underlying mechanism. Additionally, the correlations between ferroptosis and drug resistance were evaluated using the NCI-60 database.Results: A 5–hub-gene signature associated with ferroptosis was constructed by multivariate Cox regression analysis to stratify patients into two risk groups. Patients with high risk had worse prognosis than those with low risk. Multivariate Cox regression analysis uncovered that the risk score was an independent prognostic indicator. We also proved the signature’s predictive capacity using the Kaplan–Meier method and receiver operating characteristic (ROC) curve analysis. Functional analysis showed that nuclear division and the cell cycle were enriched. Immune-related analysis revealed that the signature was enriched in immune-related pathways. Moreover, the risk signature was significantly associated with immune cell infiltration, immune checkpoints, TIP-related genes, tumor stem cells, as well as m6A-related genes. Furthermore, these genes were crucial regulators of drug resistance.Conclusion: We identified and validated a novel hub gene signature that is closely associated with ferroptosis as a new and efficient biomarker with favorable potential for predicting the prognosis of HCC patients. In addition, it also offers new insights into the molecular mechanisms of HCC and provides an effective approach for the treatment of HCC. Further studies are necessary to validate the results of our study.
Identification of Immune-Related Hub Genes in Parkinson’s Disease
Authors: Chen Lin , Wang Yong , Huang Juan , Hu Binbin , Huang Wei 
Published: July 2022

Background: Parkinson’s disease (PD) is a common, age-related, and progressive neurodegenerative disease. Growing evidence indicates that immune dysfunction plays an essential role in the pathogenic process of PD. The objective of this study was to explore potential immune-related hub genes and immune infiltration patterns of PD.Method: The microarray expression data of human postmortem substantia nigra samples were downloaded from GSE7621, GSE20141, and GSE49036. Key module genes were screened via weighted gene coexpression network analysis, and immune-related genes were intersected to obtain immune-key genes. Functional enrichment analysis was performed on immune-key genes of PD. In addition to, immune infiltration analysis was applied by a single-sample gene set enrichment analysis algorithm to detect differential immune cell types in the substantia nigra between PD samples and control samples. Least absolute shrinkage and selection operator analysis was performed to further identify immune-related hub genes for PD. Receiver operating characteristic curve analysis of the immune-related hub genes was used to differentiate PD patients from healthy controls. Correlations between immune-related hub genes and differential immune cell types were assessed.Result: Our findings identified four hub genes (SLC18A2, L1CAM, S100A12, and CXCR4) and seven immune cell types (neutrophils, T follicular helper cells, myeloid-derived suppressor cells, type 1 helper cells, immature B cells, immature dendritic cells, and CD56 bright natural killer cells). The area under the curve (AUC) value of the four-gene-combined model was 0.92. The AUC values of each immune-related hub gene (SLC18A2, L1CAM, S100A12, and CXCR4) were 0.81, 0.78, 0.78, and 0.76, respectively.Conclusion: In conclusion, SLC18A2, L1CAM, S100A12, and CXCR4 were identified as being associated with the pathogenesis of PD and should be further researched.