scholarly journals Imaging Mass Spectrometry-Based Proteomic Analysis to Differentiate Melanocytic Nevi and Malignant Melanoma

Cancers ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 3197
Author(s):  
Rita Casadonte ◽  
Mark Kriegsmann ◽  
Katharina Kriegsmann ◽  
Isabella Hauk ◽  
Rolf R. Meliß ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Malignant Melanoma ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Imaging Mass Spectrometry ◽  
Independent Set ◽  
Molecular Techniques ◽  
Charge Ratio ◽  
Linear Discriminant ◽  
Melanocytic Nevi

The discrimination of malignant melanoma from benign nevi may be difficult in some cases. For this reason, immunohistological and molecular techniques are included in the differential diagnostic toolbox for these lesions. These methods are time consuming when applied subsequently and, in some cases, no definitive diagnosis can be made. We studied both lesions by imaging mass spectrometry (IMS) in a large cohort (n = 203) to determine a different proteomic profile between cutaneous melanomas and melanocytic nevi. Sample preparation and instrument setting were tested to obtain optimal results in term of data quality and reproducibility. A proteomic signature was found by linear discriminant analysis to discern malignant melanoma from benign nevus (n = 113) with an overall accuracy of >98%. The prediction model was tested in an independent set (n = 90) reaching an overall accuracy of 93% in classifying melanoma from nevi. Statistical analysis of the IMS data revealed mass-to-charge ratio (m/z) peaks which varied significantly (Area under the receiver operating characteristic curve > 0.7) between the two tissue types. To our knowledge, this is the largest IMS study of cutaneous melanoma and nevi performed up to now. Our findings clearly show that discrimination of melanocytic nevi from melanoma is possible by IMS.

Large-scale mass spectrometry data combined with demographics analysis rapidly predicts methicillin resistance in Staphylococcus aureus

2020 ◽  
Author(s):  
Zhuo Wang ◽  
Hsin-Yao Wang ◽  
Chia-Ru Chung ◽  
Jorng-Tzong Horng ◽  
Jang-Jih Lu ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Staphylococcus Aureus ◽  
Antibiotic Resistance ◽  
Large Scale ◽  
Operating Characteristic ◽  
Susceptibility Testing ◽  
Methicillin Resistance ◽  
Characteristic Curve ◽  
Mass Spectrometry Data ◽  
Treatment Efficiency

Abstract Background A mass spectrometry-based assessment of methicillin resistance in Staphylococcus aureus would have huge potential in addressing fast and effective prediction of antibiotic resistance. Since delays in the traditional antibiotic susceptibility testing, methicillin-resistant S. aureus remains a serious threat to human health. Results Here, linking a 7 years of longitudinal study from two cohorts in the Taiwan area of over 20 000 individually resolved methicillin susceptibility testing results, we identify associations of methicillin resistance with the demographics and mass spectrometry data. When combined together, these connections allow for machine-learning-based predictions of methicillin resistance, with an area under the receiver operating characteristic curve of >0.85 in both the discovery [95% confidence interval (CI) 0.88–0.90] and replication (95% CI 0.84–0.86) populations. Conclusions Our predictive model facilitates early detection for methicillin resistance of patients with S. aureus infection. The large-scale antibiotic resistance study has unbiasedly highlighted putative candidates that could improve trials of treatment efficiency and inform on prescriptions.

Can Postoperative Nausea and Vomiting Be Predicted? 

1999 ◽  
Vol 91 (1) ◽  
pp. 109-118 ◽  
Author(s):  
David R. Sinclair ◽  
Frances Chung ◽  
Gabor Mezei
Keyword(s):  
Postoperative Nausea ◽  
Operating Characteristic ◽  
Smoking Status ◽  
Characteristic Curve ◽  
Independent Set ◽  
Postoperative Nausea And Vomiting ◽  
Nausea And Vomiting ◽  
Telephone Interviews ◽  
Validation Set ◽  
Surgical Unit

Background Iletrospective studies fail to identify predictors of postoperative nausea and vomiting (PONV). The authors prospectively studied 17,638 consecutive outpatients who had surgery to identify predictors. Methods Data on medical conditions, anesthesia, surgery, and PONV were collected in the post-anesthesia care unit, in the ambulatory surgical unit, and in telephone interviews conducted 24 h after surgery. Multiple logistic regression with backward stepwise elimination was used to develop a predictive model An independent set of patients was used to validate the model Results Age (younger or older), sex (female or male), smoking status (nonsmokers or smokers), previous PONV, type of anesthesia (general or other), duration of anesthesia (longer or shorter), and type of surgery (plastic, orthopedic shoulder, or other) were independent predictors of PONV. A 10-yr increase in age decreased the likelihood of PONV by 13%. The risk for men was one third that for women. A 30-min increase in the duration of anesthesia increased the likelihood of PONV by 59%. General anesthesia increased the likelihood of PONV 11 times compared with other types of anesthesia. Patients with plastic and orthopedic shoulder surgery had a sixfold increase in the risk for PONV. The model predicted PONV accurately and yielded an area under the receiver operating characteristic curve of 0.785+/-0.011 using an independent validation set. Conclusions A validated mathematical model is provided to calculate the risk of PONV in outpatients having surgery. Knowing the factors that predict PONV will help anesthesiologists determine which patients will need antiemetic therapy.

Large Congenital Melanocytic Nevi and the Risk for Development of Malignant Melanoma and Neurocutaneous Melanocytosis

PEDIATRICS ◽  
2000 ◽  
Vol 106 (4) ◽  
pp. 736-741 ◽  
Author(s):  
F. V. Bittencourt ◽  
A. A. Marghoob ◽  
A. W. Kopf ◽  
K. L. Koenig ◽  
R. S. Bart
Keyword(s):  
Malignant Melanoma ◽  
Melanocytic Nevi ◽  
Congenital Melanocytic Nevi ◽  
Neurocutaneous Melanocytosis

A Case of Malignant Melanoma Associated with Pre-existing Melanocytic Nevi.

1992 ◽  
Vol 54 (5) ◽  
pp. 907-911
Author(s):  
Tadashige SONODA ◽  
Kazumoto KATAGIRI ◽  
Hiroto TERASHI ◽  
Sotaro KURATA ◽  
Susumu TAKAYASU ◽  
...  
Keyword(s):  
Malignant Melanoma ◽  
Melanocytic Nevi

Spatial Metabolomics of the Human Kidney Using MALDI Trapped Ion Mobility Imaging Mass Spectrometry

2020 ◽  
Author(s):  
Elizabeth Neumann ◽  
Lukasz Migas ◽  
Jamie L. Allen ◽  
Richard Caprioli ◽  
Raf Van de Plas ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Ion Mobility ◽  
Imaging Mass Spectrometry ◽  
Structural Complexity ◽  
Human Kidney ◽  
Resolving Power ◽  
Mobility Separation ◽  
Trapped Ion ◽  
Mobility Data ◽  
Ion Mobility Separation

<div> <div> <p>Small metabolites are essential for normal and diseased biological function but are difficult to study because of their inherent structural complexity. MALDI imaging mass spectrometry (IMS) of small metabolites is particularly challenging as MALDI matrix clusters are often isobaric with metabolite ions, requiring high resolving power instrumentation or derivatization to circumvent this issue. An alternative to this is to perform ion mobility separation before ion detection, enabling the visualization of metabolites without the interference of matrix ions. Here, we use MALDI timsTOF IMS to image small metabolites at high spatial resolution within the human kidney. Through this, we have found metabolites, such as arginic acid, acetylcarnitine, and choline that localize to the cortex, medulla, and renal pelvis, respectively. We have also demonstrated that trapped ion mobility spectrometry (TIMS) can resolve matrix peaks from metabolite signal and separate both isobaric and isomeric metabolites with different localizations within the kidney. The added ion mobility data dimension dramatically increased the peak capacity for molecular imaging experiments. Future work will involve further exploring the small metabolite profiles of human kidneys as a function of age, gender, and ethnicity.</p></div></div>

Serum miR-21 and miR-26a Levels Negatively Correlate with Severity of Cirrhosis in Patients with Chronic Hepatitis B

MicroRNA ◽  
2018 ◽  
Vol 8 (1) ◽  
pp. 86-92 ◽  
Author(s):  
Shili Jiang ◽  
Wei Jiang ◽  
Ying Xu ◽  
Xiaoning Wang ◽  
Yongping Mu ◽  
...  
Keyword(s):  
Chronic Hepatitis ◽  
Hepatitis B ◽  
Chronic Hepatitis B ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Curve Analysis ◽  
Pugh Class ◽  
Operating Characteristic Curve ◽  
Class C ◽  
Circulating Levels

Background and Objective: Accurately evaluating the severity of liver cirrhosis is essential for clinical decision making and disease management. This study aimed to evaluate the value of circulating levels of microRNA (miR)-26a and miR-21 as novel noninvasive biomarkers in detecting severity of cirrhosis in patients with chronic hepatitis B. </P><P> Methods: Thirty patients with clinically diagnosed chronic hepatitis B-related cirrhosis and 30 healthy individuals were selected. The serum levels of miR-26a and miR-21 were quantified by qRT-PCR. Receiver operating characteristic curve analysis was performed to evaluate the sensitivity and specificity of the miRNAs for detecting the severity of cirrhosis. Results: Serum miR-26a and miR-21 levels were found to be significantly downregulated in patients with severe cirrhosis scored at Child-Pugh class C in comparison to healthy controls (miR-26a p<0.01, and miR-21 p<0.001, respectively). The circulating miR-26a and miR-21 levels in patients were positively correlated with serum albumin concentration but negatively correlated with serum total bilirubin concentration and prothrombin time. Receiver operating characteristic curve analysis revealed that both serum miR-26a and miR-21 levels were associated with a high diagnostic accuracy for patients with cirrhosis scored at Child-Pugh class C (miR-26a Cut-off fold change at ≤0.4, Sensitivity: 84.62%, Specificity: 89.36%, P<0.0001; miR-21 Cut-off fold change at ≤0.6, Sensitivity: 84.62%, Specificity: 78.72%, P<0.0001). Our results indicate that the circulating levels of miR-26a and miR-21 are closely related to the extent of liver decompensation, and the decreased levels are capable of discriminating patients with cirrhosis at Child-Pugh class C from the whole cirrhosis cases.

A validated novel preoperative index to predict the extent of intraperitoneal contamination in patients with acute abdominal pathology: A cohort study

2019 ◽  
Vol 30 (7-8) ◽  
pp. 221-228
Author(s):  
Shahab Hajibandeh ◽  
Shahin Hajibandeh ◽  
Nicholas Hobbs ◽  
Jigar Shah ◽  
Matthew Harris ◽  
...  
Keyword(s):  
Receiver Operating Characteristic Curve ◽  
Receiver Operating Characteristic ◽  
Operating Characteristic ◽  
Validation Cohort ◽  
Characteristic Curve ◽  
Curve Analysis ◽  
Emergency Laparotomy ◽  
Contamination Index ◽  
Operating Characteristic Curve ◽  
Receiver Operating

Aims To investigate whether an intraperitoneal contamination index (ICI) derived from combined preoperative levels of C-reactive protein, lactate, neutrophils, lymphocytes and albumin could predict the extent of intraperitoneal contamination in patients with acute abdominal pathology. Methods Patients aged over 18 who underwent emergency laparotomy for acute abdominal pathology between January 2014 and October 2018 were randomly divided into primary and validation cohorts. The proposed intraperitoneal contamination index was calculated for each patient in each cohort. Receiver operating characteristic curve analysis was performed to determine discrimination of the index and cut-off values of preoperative intraperitoneal contamination index that could predict the extent of intraperitoneal contamination. Results Overall, 468 patients were included in this study; 234 in the primary cohort and 234 in the validation cohort. The analyses identified intraperitoneal contamination index of 24.77 and 24.32 as cut-off values for purulent contamination in the primary cohort (area under the curve (AUC): 0.73, P < 0.0001; sensitivity: 84%, specificity: 60%) and validation cohort (AUC: 0.83, P < 0.0001; sensitivity: 91%, specificity: 69%), respectively. Receiver operating characteristic curve analysis also identified intraperitoneal contamination index of 33.70 and 33.41 as cut-off values for feculent contamination in the primary cohort (AUC: 0.78, P < 0.0001; sensitivity: 87%, specificity: 64%) and validation cohort (AUC: 0.79, P < 0.0001; sensitivity: 86%, specificity: 73%), respectively. Conclusions As a predictive measure which is derived purely from biomarkers, intraperitoneal contamination index may be accurate enough to predict the extent of intraperitoneal contamination in patients with acute abdominal pathology and to facilitate decision-making together with clinical and radiological findings.

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