bluuebunny/crossref_metadata_2025_split huggingface dataset:
Penerapan Algoritma Apriori Terhadap Perancangan Sistem Informasi Dalam Analisis Penjualan Bahan Bangunan
Authors: Romindo  
Published: September 2022

Perusahaan yang bergerak di bidang distributor bahan bangunan dengan bahan utama besi, seperti toko bangunan. Perusahaan melakukan pencatatan data transaksi penjualan produk yang dilakukan oleh pelanggan melalui software pengolah kata. Perusahaaan tentunya membutuhkan sebuah sistem analisis yang dapat digunakan dalam menunjang proses pengambilan keputusan. Data-data perusahaan yang tercatat setiap bulannya tentunya sangat banyak dan akan menjadi data yang tidak berguna apabila tidak diolah dan dianalisis dengan baik. Salah satu cara untuk melakukan analisis terhadap sekumpulan data menjadi pengetahuan adalah melalui teknik data mining. Algoritma Apriori adalah salah satu algoritma data mining yang dapat digunakan pada penerapan market basket analysis (analisis keranjang belanja) untuk mencari aturan-aturan asosiasi yang memenuhi batas support dan confidence. Dengan itemset, seperti: Hollow Nill 20 x 20 x 0,55 total transaksi 2, Nako 10.7 x 10.7 Polos x 2,75M total transaksi 5 dan Nako 10.7 x 10.7 x 2.75M Ulir total transaksi 3, maka hasil analisis data penjualan Toko Bangunan dengan total data penjualan sebanyak 292 invoice mendapatkan nilai minimum support tertinggi yaitu 5% dan menghasilkan rule berjumlah 2. Minimum confidence tertinggi yaitu 100% dan menghasilkan rule berjumlah 3. Panjang itemset yang terbentuk yaitu 2-itemset dan 3-itemset.
Effect of Ultraviolet-C Radiation on the Morphology of Cyanobacteria Nostoc sp. LBALBR-2 Isolated from Supply Reservoir (Belém, Pará, Brazil)
Authors: Sousa Eliane Brabo de , Gomes Aline Lemos , Cunha Celly Jenniffer da Silva , Pires Paola Vitória Brito , Ahndrew Lisbethe Melo Sckyr , Costa-Tavares Vanessa Bandeira da 
Published: September 2022

Cyanobacteria are photosynthetic prokaryotic organisms that in aquatic environments can compose the phytoplankton and phytobenthos, being important in the primary production of these ecosystems. The objective of this work was to identify the main morphological variations of the cells, filaments and thallus of the cyanobacteria Nostoc sp. LBALBR-2 submitted to ultraviolet radiation (UV-C) in microcosm systems. The cyanobacteria Nostoc sp. was subjected to four treatments: 1- control treatment in nutrient medium; 2- treatment in nutrient medium with exposure to UV-C radiation; 3- control treatment in medium without nutrients and 4- treatment in medium without nutrients with exposure to UV-C radiation. Optical density and chlorophyll-a analyses were performed to determine the growth of Nostoc populations and microscopic analyses to characterize the morphological development of the species. Lack of nutrients generated short trichomes with terminal heterocytes, scattered solitary akinetes and appearance of hormogonia. On nutrient medium the trichomes of Nostoc sp. showed predominantly the vegetative serial form. Cultures exposed to UV-C produced anomalous cells, thick mucilage, fragmented trichomes and hormogonia. It is concluded that Nostoc sp. LBALBR-2 grew well under eutrophication conditions and although it showed cell deformation it was resistant to UV-C radiation.
Neuropilin-1 modulates the 3D invasive properties of glioblastoma stem-like cells
Authors: Kerhervé Mathilde , Rosińska Sara , Trillet Kilian , Zeinaty Alya , Feyeux Magalie , Nedellec Steven , Gavard Julie 
Published: September 2022

Glioblastoma multiforme (GBM) is a rare, yet devastating, primary brain tumor in adults. Current treatments remain generally ineffective and GBM almost invariably recurs, resulting in median survival of 15 months. This high malignancy sources notably from the resilience and invasive capabilities of tumor cells. Within GBM, exists a population of self-sustaining transformed cells with stem-like properties (GSCs), which are thought to be responsible for tumor initiation, growth, and invasion, as well as recurrence. In the tumor microenvironment, GSCs might be found in the vicinity of brain endothelial cells, which provide a protective habitat. Likewise, these resistant, quiescent GSCs may accumulate in hypoxic zones, away from the perivascular niche, or travel towards the healthy brain parenchyma, by eminently co-opting neuro-vascular tracks. Herein, we established an ex vivo model to explore GSC invasive behavior. We found that patient-derived cells massively invade the collagen matrix. In addition, we described that the glycoprotein Neuropilin-1 (NRP1) contributes to GSC spreading and invasion. Indeed, both RNA interference-mediated silencing and CRISPR-mediated gene editing deletion of NRP1 strongly impaired the 3D invasive properties of patient-derived GSCs and their close localization to the brain blood vessels. Of note, other typical features of GSCs, such as expansion and self-renewal were maintained. From a mechanistic standpoint, this biological effect might rely on the expression of the β3 subunit integrin cell-extracellular matrix adhesive receptor. Our data, therefore, propose a reliable approach to explore invasive properties of patient glioma cells ex vivo and identify NRP1 as a mediator in this malignant process.
Identification of immune-related hub genes and miRNA-mRNA pairs involved in immune infiltration in human septic cardiomyopathy by bioinformatics analysis
Authors: Li Jingru , Sun Guihu , Ma Haocheng , Wu Xinyu , Li Chaozhong , Ding Peng , Lu Si , Li Yanyan , Yang Ping , Li Chaguo , Yang Jun , Peng Yunzhu , Meng Zhaohui , Wang Luqiao 
Published: September 2022

AbstractSeptic cardiomyopathy (SCM) is a serious complication caused by sepsis that will further exacerbate the patient's prognosis. However, immune-related genes (IRGs) and their molecular mechanism during septic cardiomyopathy are largely unknown. Therefore, our study aims to explore the immune-related hub genes (IRHGs) and immune-related miRNA-mRNA pairs with potential biological regulation in SCM by means of bioinformatics analysis and experimental validation.MethodFirstly, screen differentially expressed mRNAs (DE-mRNAs) from the dataset GSE79962, and construct a PPI network of DE-mRNAs. Secondly, the hub genes of SCM were identified from the PPI network and the hub genes were overlapped with immune cell marker genes (ICMGs) to further obtain IRHGs in SCM. In addition, receiver operating characteristic (ROC) curve analysis was also performed in this process to determine the disease diagnostic capability of IRHGs. Finally, the crucial miRNA-IRHG regulatory network of IRHGs was predicted and constructed by bioinformatic methods. Real-time quantitative reverse transcription-PCR (qRT-PCR) and dataset GSE72380 were used to validate the expression of the key miRNA-IRHG axis.ResultThe results of immune infiltration showed that neutrophils, Th17 cells, Tfh cells, and central memory cells in SCM had more infiltration than the control group; A total of 2 IRHGs were obtained by crossing the hub gene with the ICMGs, and the IRHGs were validated by dataset and qRT-PCR. Ultimately, we obtained the IRHG in SCM: THBS1. The ROC curve results of THBS1 showed that the area under the curve (AUC) was 0.909. Finally, the miR-222-3p/THBS1 axis regulatory network was constructed.ConclusionIn summary, we propose that THBS1 may be a key IRHG, and can serve as a biomarker for the diagnosis of SCM; in addition, the immune-related regulatory network miR-222-3p/THBS1 may be involved in the regulation of the pathogenesis of SCM and may serve as a promising candidate for SCM therapy.
Deep-learning-based post-processing for probabilistic precipitation forecasting
Authors: Ji Yan , Zhi Xiefei , Ji Luying , Zhang Yingxin , Hao Cui , Peng Ting 
Published: September 2022

Ensemble prediction systems (EPSs) serve as a popular technique to provide probabilistic precipitation prediction in short- and medium-range forecasting. However, numerical models still suffer from imperfect configurations associated with data assimilation and physical parameterization, which can lead to systemic bias. Even state-of-the-art models often fail to provide high-quality precipitation forecasting, especially for extreme events. In this study, two deep-learning-based models—a shallow neural network (NN) and a deep NN with convolutional layers (CNN)—were used as alternative post-processing approaches to further improve the probabilistic forecasting of precipitation over China with 1–7 lead days. A popular conventional method—the censored and shifted gamma distribution-based ensemble model output statistics (CSG EMOS)—was used as the baseline. Re-forecasts run using a frozen EPS—Global Ensemble Forecast System version 12—were collected as the raw ensembles spanning from 2000 to 2019. The re-forecast data were generated once per day and consisted of one control run and four perturbed members. We used the calendar year 2018 as the validation period and 2019 as the testing period, and the remaining 18 years of data were used for training. According to the results, in terms of the continuous ranked probability score (CRPS) and the Brier score, the CNN model significantly outperforms the shallow NN model, as well as the CSG EMOS approach and the raw ensemble, especially for heavy or extreme precipitation events (those exceeding 50 mm/day). A remarkable degradation was seen when reducing the size of training samples from 18 years of data to two years. The spatial distribution of the CRPS shows that the stations in central China were better calibrated than those in other regions. With a lead time of 1 day, the CNN model was found to be superior to the other models (in terms of the CRPS) at 74.5% of the study stations. These results indicate that deep NNs can serve as a promising approach to the statistical post-processing of probabilistic precipitation forecasting.
Analysis of detrended fluctuation function derived from continuous glucose monitoring may assist in distinguishing latent autoimmune diabetes in adults from T2DM
Authors: Zhang Liyin , Tian Qi , Guo Keyu , Wu Jieru , Ye Jianan , Ding Zhiyi , Zhou Qin , Huang Gan , Li Xia , Zhou Zhiguang , Yang Lin 
Published: September 2022

BackgroundWe aimed to explore the performance of detrended fluctuation function (DFF) in distinguishing patients with latent autoimmune diabetes in adults (LADA) from type 2 diabetes mellitus (T2DM) with glucose data derived from continuous glucose monitoring.MethodsIn total, 71 LADA and 152 T2DM patients were enrolled. Correlations between glucose parameters including time in range (TIR), mean glucose, standard deviation (SD), mean amplitude of glucose excursions (MAGE), coefficient of variation (CV), DFF and fasting and 2-hour postprandial C-peptide (FCP, 2hCP) were analyzed and compared. Receiver operating characteristics curve (ROC) analysis and 10-fold cross-validation were employed to explore and validate the performance of DFF in diabetes classification respectively.ResultsPatients with LADA had a higher mean glucose, lower TIR, greater SD, MAGE and CV than those of T2DM (P&lt;0.001). DFF achieved the strongest correlation with FCP (r = -0.705, P&lt;0.001) as compared with TIR (r = 0.485, P&lt;0.001), mean glucose (r = -0.337, P&lt;0.001), SD (r = -0.645, P&lt;0.001), MAGE (r = -0.663, P&lt;0.001) and CV (r = -0.639, P&lt;0.001). ROC analysis showed that DFF yielded the greatest area under the curve (AUC) of 0.862 (sensitivity: 71.2%, specificity: 84.9%) in differentiating LADA from T2DM as compared with TIR, mean glucose, SD, MAGE and CV (AUC: 0.722, 0.650, 0.800, 0.820 and 0.807, sensitivity: 71.8%, 47.9%, 63.6%, 72.7% and 78.8%, specificity: 67.8%, 83.6%, 80.9%, 80.3% and 72.4%, respectively). The kappa test indicated a good consistency between DFF and the actual diagnosis (kappa = 0.551, P&lt;0.001). Ten-fold cross-validation showed a stable performance of DFF with a mean AUC of 0.863 (sensitivity: 78.8%, specificity: 77.8%) in 10 training sets and a mean AUC of 0.866 (sensitivity: 80.9%, specificity: 84.1%) in 10 test sets.ConclusionsA more violent glucose fluctuation pattern was marked in patients with LADA than T2DM. We first proposed the possible role of DFF in distinguishing patients with LADA from T2DM in our study population, which may assist in diabetes classification.
Lipid droplet accumulation in β cells in patients with type 2 diabetes is associated with insulin resistance, hyperglycemia and β cell dysfunction involving decreased insulin granules
Authors: Horii Tomomi , Kozawa Junji , Fujita Yukari , Kawata Satoshi , Ozawa Harutoshi , Ishibashi Chisaki , Yoneda Sho , Nammo Takao , Miyagawa Jun-ichiro , Eguchi Hidetoshi , Shimomura Iichiro 
Published: September 2022

Background and objectivePancreatic fat is a form of ectopic fat. Lipid droplets (LDs) are also observed in β cells; however, the pathophysiological significance, especially for β cell function, has not been elucidated. Our aim was to assess LD accumulation in β cells in various stages of glucose intolerance and to clarify its relationship with clinical and histological parameters.MethodsWe examined 42 Japanese patients who underwent pancreatectomy. The BODIPY493/503-positive (BODIPY-positive) area in β cells was measured in pancreatic sections from 32 patients. The insulin granule numbers were counted in an additional 10 patients using electron microscopy.ResultsThe BODIPY-positive area in β cells in preexisting type 2 diabetes patients was higher than that in normal glucose tolerance patients (p = 0.031). The BODIPY-positive area in β cells was positively correlated with age (r = 0.45, p = 0.0097), HbA1c (r = 0.38, p = 0.0302), fasting plasma glucose (r = 0.37, p = 0.045), and homeostasis model assessment insulin resistance (r = 0.41, p = 0.049) and negatively correlated with an increase in the C-peptide immunoreactivity level by the glucagon test (r = -0.59, p = 0.018). The ratio of mature insulin granule number to total insulin granule number was reduced in the patients with rich LD accumulation in β cells (p = 0.039).ConclusionsType 2 diabetes patients had high LD accumulation in β cells, which was associated with insulin resistance, hyperglycemia, aging and β cell dysfunction involving decreased mature insulin granules.
Occurrence and risk assessment of organotin compounds in the surface water of the upper Yangtze River Estuary
Authors: Dai Qi , Chen Ling , Li Pan , Xia Shengji , Wang Yanyan , Huang Qinghui 
Published: September 2022

Organotin compounds (OTCs) are a category of persistent toxic substances with endocrine disrupting effects and may pose a risk to aquatic organisms and human health via water. This study collected 78 surface water samples from the drinking water source in the upper Yangtze River Estuary from July 2018 to November 2019. Out of the nine OTC targets, tributyltin (TBT), dimethyltin (DMT), trimethyltin (TMT), dibutyltin (DBT), and monobutyltin (MBT) were detected from more than 50% of the water samples, with cumulative concentrations of OTCs ranging from 42.5 ± 54.0 to 421 ± 176 ng Sn L−1. The composition and concentrations of OTCs in the stormy months were different from those in other months. The concentrations of OTCs with the ebbing tide exceeded those in the flooding tide and increased when the flooding tide transitioned to the ebbing tide. A pulsed trend in concentrations of OTCs in river water was evident due to the impact of rainfall runoff and tidal currents. Identified sources of OTCs included ship antifouling paints, agricultural pesticides, and plastic waste. TBT in water sources poses a low risk to human health and a risk to the ecosystem, particularly during the stormy months.
The expression and methylation of PITX genes is associated with the prognosis of head and neck squamous cell carcinoma
Authors: Zhao Yaqiong , Zhao Jie , Zhong Mengmei , Zhang Qian , Yan Fei , Feng Yunzhi , Guo Yue 
Published: September 2022

Background: The PITX gene family, comprising PITX1, PITX2, and PITX3, is critical in organogenesis and has been evolutionary conserved in animals. PITX genes are associated with the advanced progression and poor prognosis of multiple cancers. However, the relationship between the PITX genes and head and neck squamous cell carcinoma (HNSC) has not been reported.Methods: We used data from The Cancer Genome Atlas (TCGA) to analyze the association between PITX mRNA expression and clinicopathological parameters of patients with HNSC. The prognostic value of PITX genes was evaluated using the Kaplan-Meier plotter. Multivariate Cox analysis was used to screen out prognosis-associated genes to identify better prognostic indicators. The potential roles of PITX1 and PITX2 in HNSC prognosis were investigated using the protein-protein interaction (PPI) network, Gene Ontology (GO) analysis, and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. The correlation between PITX1 and PITX2 expression or methylation and immune cell infiltration was evaluated using the tumor-immune system interaction database (TISIDB). MethSurv was used to identify DNA methylation and its effect on HNSC prognosis.Results:PITX genes expression was correlated with different cancers. PITX1 and PITX2 expression was lower in the patients with HNSC. In HNSC, PITX1 expression was significantly related to the clinical stage, histologic grade, and N stage, while PITX2 expression was only significantly related to the histologic grade. The high expression of PITX3 was significantly related to the histologic grade, T stage, and N stage. Survival analysis revealed that PITX genes had prognostic value in HNSC, which was supported by multivariate Cox analysis. PPI network and enrichment analysis showed that the genes interacting with PITX1 and PITX2 belonged predominantly to signaling pathways associated with DNA binding and transcription. Of the CpG DNA methylation sites in PITX1 and PITX2, 28 and 22 were related to the prognosis of HNSC, respectively. Additionally, PITX1 and PITX2 expression and methylation was associated with tumor-infiltrating lymphocytes (TILs).Conclusion: The PITX genes were differentially expressed in patients with HNSC, highlighting their essential role in DNA methylation and tumor-infiltrating immune cell regulation, as well as overall prognostic value in HNSC.
Immunological risk factors for sepsis-associated delirium and mortality in ICU patients
Authors: Lei Wen , Ren Zhiyao , Su Jun , Zheng Xinglong , Gao Lijuan , Xu Yudai , Deng Jieping , Xiao Chanchan , Sheng Shuai , Cheng Yu , Ma Tianshun , Liu Yu , Wang Pengcheng , Luo Oscar Junhong , Chen Guobing , Wang Zhigang 
Published: September 2022

BackgroundA major challenge in intervention of critical patients, especially sepsis-associated delirium (SAD) intervention, is the lack of predictive risk factors. As sepsis and SAD are heavily entangled with inflammatory and immunological processes, to identify the risk factors of SAD and mortality in the intensive care unit (ICU) and determine the underlying molecular mechanisms, the peripheral immune profiles of patients in the ICU were characterized.MethodsThis study contains a cohort of 52 critical patients who were admitted to the ICU of the First Affiliated Hospital of Jinan University. Comorbidity, including sepsis and SAD, of this cohort was diagnosed and recorded. Furthermore, peripheral blood samples were collected on days 1, 3, and 5 of admission for peripheral immune profiling with blood routine examination, flow cytometry, ELISA, RNA-seq, and qPCR.ResultsThe patients with SAD had higher mortality during ICU admission and within 28 days of discharge. Compared with survivors, nonsurvivors had higher neutrophilic granulocyte percentage, higher CRP concentration, lower monocyte count, lower monocyte percentage, lower C3 complement level, higher CD14loCD16+ monocytes percentage, and higher levels of IL-6 and TNFα. The CD14hiCD16- monocyte percentage manifested favorable prediction values for the occurrence of SAD. Differentially expressed genes between the nonsurvival and survival groups were mainly associated with immune response and metabolism process. The longitudinal expression pattern of SLC2A1 and STIMATE were different between nonsurvivors and survivors, which were validated by qPCR.ConclusionsNonsurvival critical patients have a distinct immune profile when compared with survival patients. CD14hiCD16- monocyte prevalence and expression levels of SLC2A1 and STIMATE may be predictors of SAD and 28-day mortality in ICU patients.
T cell receptor excision circles are potential predictors of survival in adult allogeneic hematopoietic stem cell transplantation recipients with acute myeloid leukemia
Authors: Söderström Anna , Vonlanthen Sofie , Jönsson-Videsäter Kerstin , Mielke Stephan , Lindahl Hannes , Törlén Johan , Uhlin Michael 
Published: September 2022

BackgroundLymphocyte neogenesis from primary lymphoid organs is essential for a successful reconstitution of immunity after allogeneic hematopoietic stem cell transplantation (HSCT). This single-center retrospective study aimed to evaluate T cell receptor excision circles (TREC) and kappa-deleting recombination excision circles (KREC) as surrogate markers for T and B cell recovery, as predictors for transplantation-related outcomes in adult acute myeloid leukemia (AML) patients.MethodsNinety adult patients diagnosed with AML and treated with HSCT between 2010 and 2015 were included in the study. TREC and KREC levels were measured by quantitative PCR at 1, 3, 6, and 12 months after transplantation.ResultsOverall, excision circle levels increased between 3 and 6 months post-HSCT for TREC (p = 0.005) and 1 and 3 months for KREC (p = 0.0007). In a landmark survival analysis at 12 months post-HSCT, TREC levels were associated with superior overall survival (HR: 0.52, 95% CI: 0.34 - 0.81, p = 0.004). The incidence of viral infections within the first 100 days after transplantation was associated with lower TREC levels at 6 months (p = 0.0002). CMV reactivation was likewise associated with lower TREC levels at 6 months (p = 0.02) post-HSCT. KREC levels were not associated with clinical outcomes in statistical analyzes.ConclusionsResults from the present study indicate that TREC measurement could be considered as part of the post-HSCT monitoring to identify AML patients with inferior survival after transplantation. Further prospective studies are warranted to validate these findings.
Versican enrichment predicts poor prognosis and response to adjuvant therapy and immunotherapy in gastric cancer
Authors: Song Junquan , Wei Rongyuan , Huo Shiying , Liu Chenchen , Liu Xiaowen 
Published: September 2022

BackgroundIncreasing evidence has revealed an important role of versican (VCAN) on various aspects of cancer progression. Here, we assessed the impact of VCAN expression on prognosis and the response to adjuvant therapy and immunotherapy in patients with gastric cancer (GC).MethodsFour independent cohorts containing 1353 patients with GC, were utilized to investigate the effect of VCAN expression on prognosis and response to adjuvant therapy in GC. Two cohorts treated with immune checkpoint blockades were included to assess the predict value of VCAN expression on response to immunotherapy. Moreover, the bulk RNA-seq and single-cell RNA-seq data were analyzed to illustrate the role of VCAN in tumor microenvironment. Clinical outcomes of patient subgroups were compared by Kaplan-Meier curves with the log-rank test.ResultHigh VCAN expression was associated with poor prognosis for patients with GC. Compared with patients with high VCAN expression, patients with low VCAN expression benefited more from adjuvant chemotherapy and adjuvant chemoradiotherapy. Moreover, patients with high VCAN expression tended to be resistant to immunotherapy, and VCAN could serve as a promising indicator for predicting the response to immunotherapy. VCANhigh tumors showed a specific microenvironment with more cancer associated fibroblasts infiltration and significant enrichment of stromal relevant signaling pathways.ConclusionVCAN could predict the response to adjuvant chemotherapy, adjuvant chemoradiotherapy and immunotherapy in GC, and designing new medicine target to VCAN might be an effective way to improve the efficacy of several treatment options for GC.