Implication of efflux pumps and ERG11 genes in resistance of clinical Trichosporon asahii isolates to fluconazole

Introduction. Trichosporon asahii has been recognized as an opportunistic agent having a limited sensitivity to antifungal treatment. Hypothesis/Gap Statement. Molecular mechanisms of azole resistance have been rarely reported for Trichosproron asahii. Similar to other fungi, we hypothesized that both ERG11 gene mutation and efflux pumps genes hyper-expression were implicated. Aim. The current work aimed to study the sensitivity of clinical T. asahii isolates to different antifungal agents and to explore their resistance mechanisms by molecular methods including real-time PCR and gene sequencing. Methods. The sensitivity of T. asahii isolates to fluconazole, amphotericin B and voriconazole was estimated by the Etest method. Real-time PCR was used to measure the relative expression of Pdr11, Mdr and ERG11 genes via the ACT1 housekeeping gene. Three pairs of primers were also chosen to sequence the ERG11 gene. This exploration was followed by statistical study including the receiver operating characteristic (ROC) curve analysis to identify a relationship between gene mean expression and the sensitivity of isolates. Results. In 31 clinical isolates, the resistance frequencies were 87, 16.1 and 3.2 %, respectively, for amphotericin B, fluconazole and voriconazole. Quantitative real-time PCR demonstrated that only Mdr over-expression was significantly associated with FCZ resistance confirmed by univariate statistical study and the ROC curve analysis (P <0.05). The ERG11 sequencing revealed two mutations H380G and S381A in TN325U11 (MIC FCZ=8 µg ml−1) and H437R in TN114U09 (MIC FCZ=256 µg ml−1) in highly conserved regions (close to the haem-binding domain) but their involvement in the resistance mechanism has not yet been assigned. Conclusion. T. asahii FCZ resistance mechanisms are proven to be much more complex and gene alteration sequence and/or expression can be involved. Only Mdr gene over-expression was significantly associated with FCZ resistance and no good correlation was observed between FCZ and VCZ MIC values and relative gene expression. ERG11 sequence alteration seems to play a major role in T. asahii FCZ resistance mechanism but their involvement needs further confirmation.

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The effect of BKV reactivation on cytokines behavior in kidney transplanted patients

BMC Nephrology ◽

10.1186/s12882-021-02645-y ◽

2022 ◽

Vol 23 (1) ◽

Author(s):

Zahra Rahimi ◽

Ramin Yaghobi ◽

Afsoon Afshari ◽

Jamshid Roozbeh ◽

Mohammad Javad Mokhtari ◽

...

Keyword(s):

Real Time ◽

Roc Curve ◽

Real Time Pcr ◽

Curve Analysis ◽

Expression Level ◽

Control Group ◽

Roc Curve Analysis ◽

Tnf Α ◽

Ifn Γ ◽

Inactive Group

Abstract Background BK virus associated nephropathy (BKVAN) is one of the common causes of graft loss among kidney transplanted recipients (KTRs). The current treatment for BKV nephropathy is decreasing the immunosuppressive regimen in KTRs. Interleukin-27 (IL-27) is a multifunctional cytokine that might be the front-runner of an important pathway in this regard. Therefore, in current study it is tried to evaluate the changes in the expression level of IL-27 and some related molecules, resulting from BKV reactivation in KTR patients. Methods EDTA-treated blood samples were collected from all participants. Patients were divided into two groups, 31 kidney transplant recipients with active and 32 inactive BKV infection, after being monitored by Real time PCR (Taq-Man) in plasma. Total of 30 normal individuals were considered as healthy control group. Real time PCR (SYBR Green) technique is used to determine the expression level of studied genes. Results The results of gene expression comparisons showed that the expression level of IL-27, IFN-γ, TNF-α, TNFR2 and IRF7 genes was significantly higher in inactive group in comparison to active group. The expression level of TLR4 was lower in both active and inactive groups in comparison to control group. ROC curve analysis showed that IL-27 and IRF7 are significantly different amongst other studied genes. Finally, the analyses revealed that the expression level of most of the studied genes (except for TNF-α and TLR4) have significant correlation with viral load. Conclusions Our findings revealed that IL-27, IFN-γ, TNF-α, TNFR2 and IRF7 expression level is higher in inactive group and TLR4 expression level is lower in patients’ groups in comparison to control group. Also, ROC curve analysis showed IL-27 and IRF7 can significantly differentiate studied groups (BKV active vs. inactive). Therefore, these results might help elucidating the pattern in charge of BKV reactivation in kidney transplanted patients.

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Identification of MCM4 as a Prognostic Marker of Hepatocellular Carcinoma

BioMed Research International ◽

10.1155/2021/7479326 ◽

2021 ◽

Vol 2021 ◽

pp. 1-14

Author(s):

Huandi Zhou ◽

Le Jiang ◽

Guohui Wang ◽

Linlin Su ◽

Liubing Hou ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Real Time ◽

Roc Curve ◽

Real Time Pcr ◽

Malignant Tumors ◽

Nodal Metastasis ◽

Cellular Heterogeneity ◽

Survival Prediction ◽

Roc Curve Analysis ◽

Potential Biomarker

Object. Hepatocellular carcinoma is one of the most common malignant tumors worldwide owing to its complicated molecular and cellular heterogeneity and its high incidence rate every year. It is an urgent need to search for new efficient molecular markers of HCC to reduce mortality and improve HCC prognosis. In this article, MCM4, a member of a family of proteins closely related to DNA replication and cell proliferation, was selected as a potential biomarker of HCC prognosis. Methods. MCM4 expression difference in HCC were analyzed from TCGA and GEO data and verified by real-time PCR and western blot. ROC curve was used to analyze the diagnostic value of MCM4 and AFP. Additionally, the relationship between MCM4 and stage or nodal metastasis status or grade or age in TCGA cohort with HCC was observed from the UALCAN website. The univariate and multivariate Cox and functional analyses were done to explore the prognostic value of MCM4 in TCGA cohort. Results. It was found that MCM4 was significantly highly expressed in HCC tissues from TCGA, GEO, and experimental data. Furthermore, ROC curve analysis showed that MCM4 was superior to be a diagnostic biomarker than AFP from TCGA ( AU C MCM 4 = 0.9461 , AU C AFP = 0.7056 ) and GEO (GSE19665: AU C MCM 4 = 0.8800 , AU C AFP = 0.5100 ; GSE64041 AU C MCM 4 = 0.8038 , AU C AFP = 0.6304 ). AUC of MCM4 from real-time PCR result in 60 pairs of HCC and adjacent tissues was 0.7172, demonstrating the prediction value of MCM4. Besides, different expression tendencies of MCM4 among different stages or nodal metastasis status or grade or age were observed from the UALCAN website. In addition, multiROC analysis showed the advantage of MCM4 as a survival prediction at 1, 3, and 5 years with the higher AUC at 0.69 of 1 year, 0.65 of 3 years, and 0.61 of 5 years. It was shown that MCM4 was independently associated with OS in univariate and multivariate Cox analysis. And GSEA displayed that MCM4 was highly enriched in KEGG_CELL_CYCLE signaling pathway following higher correlation positively with CDC6, PLK1, CRC1, and BUB1B in HCC. Conclusion. MCM4 might be a potential biomarker in guiding the prognostic status of HCC patients.

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Statistical Entropy Measures in C4.5 Trees

International Journal of Data Warehousing and Mining ◽

10.4018/ijdwm.2018010101 ◽

2018 ◽

Vol 14 (1) ◽

pp. 1-14 ◽

Cited By ~ 2

Author(s):

Aldo Ramirez Arellano ◽

Juan Bory-Reyes ◽

Luis Manuel Hernandez-Simon

Keyword(s):

Roc Curve ◽

Operating Characteristic ◽

Statistical Study ◽

Large Datasets ◽

Curve Analysis ◽

Statistical Entropy ◽

Roc Curve Analysis ◽

Hybrid Approaches ◽

Entropy Measures ◽

Parametric Algorithms

The main goal of this article is to present a statistical study of decision tree learning algorithms based on the measures of different parametric entropies. Partial empirical evidence is presented to support the conjecture that the parameter adjusting of different entropy measures might bias the classification. Here, the receiver operating characteristic (ROC) curve analysis, precisely, the area under the ROC curve (AURC) gives the best criterion to evaluate decision trees based on parametric entropies. The authors emphasize that the improvement of the AURC relies on of the type of each dataset. The results support the hypothesis that parametric algorithms are useful for datasets with numeric and nominal, but not for mixed, attributes; thus, four hybrid approaches are proposed. The hybrid algorithm, which is based on Renyi entropy, is suitable for nominal, numeric, and mixed datasets. Moreover, it requires less time when the number of nodes is reduced, when the AURC is maintaining or increasing, thus it is preferable in large datasets.

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MiR-144-3p Inhibits BMSC Proliferation and Osteogenic Differentiation Via Targeting FZD4 in Steroid-Associated Osteonecrosis

Current Pharmaceutical Design ◽

10.2174/1381612825666190930094019 ◽

2020 ◽

Vol 25 (45) ◽

pp. 4806-4812 ◽

Cited By ~ 3

Author(s):

Zhibo Sun ◽

Fei Wu ◽

Yue Yang ◽

Feng Liu ◽

Fengbo Mo ◽

...

Keyword(s):

Real Time ◽

Real Time Pcr ◽

Nuclear Translocation ◽

Bone Diseases ◽

Luciferase Reporter ◽

Reporter Assay ◽

Alizarin Red ◽

Over Expression ◽

Negative Effect ◽

Proliferation Ability

Background: MicroRNAs have recently been recognized to be engaged in the development of bone diseases. Objective: This study was performed to elucidate the effects of miR-144-3p on proliferation and osteogenesis of mesenchymal stem cells (MSCs) from the patients with steroid-associated osteonecrosis (ONFH) and its related mechanism. Method: The expression level of miR-144-3p in the MSCs from the proximal femur of the patients was examined by Real-time PCR. The cell proliferation ability was assayed by MTT. The differentiation ability of MSCs was assayed by Alizarin Red S (ARS) staining. The interaction between miR-144-3p and frizzled4 (FZD4) was investigated by Real-time PCR, western blot and luciferase reporter assay. Results: ONFH samples had the obviously high expression of miR-144-3p compared to the control. MiR-144-3p had a negative effect on the proliferation and osteogenesis of MSCs. Via targeting FZD4, miR-144-3p decreased β-catenin nuclear translocation, the transcription of RUNX2 and COL1A1. Over-expression of FZD4 partially reversed miR-144-3p-induced decrease in the proliferation and osteogenesis of MSCs. Conclusion: MiR-144-3p might play an important role in the development of ONFH and might be used as a novel class of therapeutic targets for this disease.

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Acute heart failure: predicting early in-hospital outcomes

European Journal of Preventive Cardiology ◽

10.1093/eurjpc/zwab061.019 ◽

2021 ◽

Vol 28 (Supplement_1) ◽

Author(s):

M Santos ◽

S Paula ◽

I Almeida ◽

H Santos ◽

H Miranda ◽

...

Keyword(s):

Heart Failure ◽

Logistic Regression ◽

Acute Heart Failure ◽

Roc Curve ◽

Real Life ◽

Study Data ◽

Curve Analysis ◽

Older Age ◽

Invasive Ventilation ◽

Roc Curve Analysis

Abstract Funding Acknowledgements Type of funding sources: None. Introduction Patients (P) with acute heart failure (AHF) are a heterogeneous population. Risk stratification at admission may help predict in-hospital complications and needs. The Get With The Guidelines Heart Failure score (GWTG-HF) predicts in-hospital mortality (M) of P admitted with AHF. ACTION ICU score is validated to estimate the risk of complications requiring ICU care in non-ST elevation acute coronary syndromes. Objective To validate ACTION-ICU score in AHF and to compare ACTION-ICU to GWTG-HF as predictors of in-hospital M (IHM), early M [1-month mortality (1mM)] and 1-month readmission (1mRA), using real-life data. Methods Based on a single-center retrospective study, data collected from P admitted in the Cardiology department with AHF between 2010 and 2017. P without data on previous cardiovascular history or uncompleted clinical data were excluded. Statistical analysis used chi-square, non-parametric tests, logistic regression analysis and ROC curve analysis. Results Among the 300 P admitted with AHF included, mean age was 67.4 ± 12.6 years old and 72.7% were male. Systolic blood pressure (SBP) was 131.2 ± 37.0mmHg, glomerular filtration rate (GFR) was 57.1 ± 23.5ml/min. 35.3% were admitted in Killip-Kimball class (KKC) 4. ACTION-ICU score was 10.4 ± 2.3 and GWTG-HF was 41.7 ± 9.6. Inotropes’ usage was necessary in 32.7% of the P, 11.3% of the P needed non-invasive ventilation (NIV), 8% needed invasive ventilation (IV). IHM rate was 5% and 1mM was 8%. 6.3% of the P were readmitted 1 month after discharge. Older age (p < 0.001), lower SBP (p = 0,035) and need of inotropes (p < 0.001) were predictors of IHM in our population. As expected, patients presenting in KKC 4 had higher IHM (OR 8.13, p < 0.001). Older age (OR 1.06, p = 0.002, CI 1.02-1.10), lower SBP (OR 1.01, p = 0.05, CI 1.00-1.02) and lower left ventricle ejection fraction (LVEF) (OR 1.06, p < 0.001, CI 1.03-1.09) were predictors of need of NIV. None of the variables were predictive of IV. LVEF (OR 0.924, p < 0.001, CI 0.899-0.949), lower SBP (OR 0.80, p < 0.001, CI 0.971-0.988), higher urea (OR 1.01, p < 0.001, CI 1.005-1.018) and lower sodium (OR 0.92, p = 0.002, CI 0.873-0.971) were predictors of inotropes’ usage. Logistic regression showed that GWTG-HF predicted IHM (OR 1.12, p < 0.001, CI 1.05-1.19), 1mM (OR 1.10, p = 1.10, CI 1.04-1.16) and inotropes’s usage (OR 1.06, p < 0.001, CI 1.03-1.10), however it was not predictive of 1mRA, need of IV or NIV. Similarly, ACTION-ICU predicted IHM (OR 1.51, p = 0.02, CI 1.158-1.977), 1mM (OR 1.45, p = 0.002, CI 1.15-1.81) and inotropes’ usage (OR 1.22, p = 0.002, CI 1.08-1.39), but not 1mRA, the need of IV or NIV. ROC curve analysis revealed that GWTG-HF score performed better than ACTION-ICU regarding IHM (AUC 0.774, CI 0.46-0-90 vs AUC 0.731, CI 0.59-0.88) and 1mM (AUC 0.727, CI 0.60-0.85 vs AUC 0.707, CI 0.58-0.84). Conclusion In our population, both scores were able to predict IHM, 1mM and inotropes’s usage.

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High‐throughput identification and quantification of Vagococcus salmoninarum by SYBR Green I‐based real‐time PCR combined with melting curve analysis

Journal of Fish Diseases ◽

10.1111/jfd.13053 ◽

2019 ◽

Vol 42 (10) ◽

pp. 1359-1368 ◽

Cited By ~ 4

Author(s):

Yolanda Torres‐Corral ◽

Clara Fernández‐Álvarez ◽

Ysabel Santos

Keyword(s):

Real Time ◽

High Throughput ◽

Real Time Pcr ◽

Melting Curve ◽

Curve Analysis ◽

Sybr Green ◽

Sybr Green I ◽

Melting Curve Analysis ◽

Identification And Quantification

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Presepsin values and prognostic nutritional index predict mortality in intensive care unit patients with sepsis: a pilot study

BMC Research Notes ◽

10.1186/s13104-021-05659-9 ◽

2021 ◽

Vol 14 (1) ◽

Author(s):

Yuichiro Shimoyama ◽

Osamu Umegaki ◽

Noriko Kadono ◽

Toshiaki Minami

Keyword(s):

Multivariate Analysis ◽

Roc Curve ◽

Operating Characteristic ◽

Prognostic Nutritional Index ◽

Early Mortality ◽

Curve Analysis ◽

Rank Test ◽

Roc Curve Analysis ◽

Log Rank Test ◽

Nutritional Index

Abstract Objective Sepsis is a major cause of mortality for critically ill patients. This study aimed to determine whether presepsin values can predict mortality in patients with sepsis. Results Receiver operating characteristic (ROC) curve analysis, Log-rank test, and multivariate analysis identified presepsin values and Prognostic Nutritional Index as predictors of mortality in sepsis patients. Presepsin value on Day 1 was a predictor of early mortality, i.e., death within 7 days of ICU admission; ROC curve analysis revealed an AUC of 0.84, sensitivity of 89%, and specificity of 77%; and multivariate analysis showed an OR of 1.0007, with a 95%CI of 1.0001–1.0013 (p = 0.0320).

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Soluble cytotoxic T-lymphocyte–associated antigen 4 (sCTLA-4) as a potential biomarker for diagnosis and evaluation of the prognosis in Glioma

BMC Immunology ◽

10.1186/s12865-021-00422-y ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Jiajia Liu ◽

Xiaoyi Tian ◽

Yan Wang ◽

Xixiong Kang ◽

Wenqi Song

Keyword(s):

T Lymphocyte ◽

Roc Curve ◽

Cytotoxic T Lymphocyte ◽

Tumor Grade ◽

Curve Analysis ◽

Enzyme Linked Immunosorbent Assay ◽

Low Grade ◽

High Grade ◽

Healthy Individuals ◽

Roc Curve Analysis

Abstract Background The cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) is widely considered as a pivotal immune checkpoint molecule to suppress antitumor immunity. However, the significance of soluble CTLA-4 (sCTLA-4) remains unclear in the patients with brain glioma. Here we aimed to investigate the significance of serum sCTLA-4 levels as a noninvasive biomarker for diagnosis and evaluation of the prognosis in glioma patients. Methods In this study, the levels of sCTLA-4 in serum from 50 patients diagnosed with different grade gliomas including preoperative and postoperative, and 50 healthy individuals were measured by an enzyme-linked immunosorbent assay (ELISA). And then ROC curve analysis and survival analyses were performed to explore the clinical significance of sCTLA-4. Results Serum sCTLA-4 levels were significantly increased in patients with glioma compared to that of healthy individuals, and which was also positively correlated with the tumor grade. ROC curve analysis showed that the best cutoff value for sCTLA-4 for glioma is 112.1 pg/ml, as well as the sensitivity and specificity with 82.0 and 78.0%, respectively, and a cut-off value of 220.43 pg/ml was best distinguished in patients between low-grade glioma group and high-grade glioma group with sensitivity 73.1% and specificity 79.2%. Survival analysis revealed that the patients with high sCTLA-4 levels (> 189.64 pg/ml) had shorter progression-free survival (PFS) compared to those with low sCTLA-4 levels (≤189.64 pg/ml). In the univariate analysis, elder, high-grade tumor, high sCTLA-4 levels and high Ki-67 index were significantly associated with shorter PFS. In the multivariate analysis, sCTLA-4 levels and tumor grade remained an independent prognostic factor. Conclusion These findings indicated that serum sCTLA-4 levels play a critical role in the pathogenesis and development of glioma, which might become a valuable predictive biomarker for supplementary diagnosis and evaluation of the progress and prognosis in glioma.

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Predictive CT features for the diagnosis of primary pulmonary mucoepidermoid carcinoma: comparison with squamous cell carcinomas and adenocarcinomas

Cancer Imaging ◽

10.1186/s40644-020-00375-2 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Xiaohua Ban ◽

Xinping Shen ◽

Huijun Hu ◽

Rong Zhang ◽

Chuanmiao Xie ◽

...

Keyword(s):

Logistic Regression ◽

Roc Curve ◽

Multinomial Logistic Regression ◽

Univariate Analysis ◽

Ct Imaging ◽

Squamous Cell Carcinomas ◽

Curve Analysis ◽

Imaging Features ◽

Roc Curve Analysis ◽

Ct Features

Abstract Background To determine the predictive CT imaging features for diagnosis in patients with primary pulmonary mucoepidermoid carcinomas (PMECs). Materials and methods CT imaging features of 37 patients with primary PMECs, 76 with squamous cell carcinomas (SCCs) and 78 with adenocarcinomas were retrospectively reviewed. The difference of CT features among the PMECs, SCCs and adenocarcinomas was analyzed using univariate analysis, followed by multinomial logistic regression and receiver operating characteristic (ROC) curve analysis. Results CT imaging features including tumor size, location, margin, shape, necrosis and degree of enhancement were significant different among the PMECs, SCCs and adenocarcinomas, as determined by univariate analysis (P < 0.05). Only lesion location, shape, margin and degree of enhancement remained independent factors in multinomial logistic regression analysis. ROC curve analysis showed that the area under curve of the obtained multinomial logistic regression model was 0.805 (95%CI: 0.704–0.906). Conclusion The prediction model derived from location, margin, shape and degree of enhancement can be used for preoperative diagnosis of PMECs.

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