Isotope pattern deconvolution as a successful alternative to calibration curve for application in wastewater-based epidemiology

SUMMARY Since 1949 about 10,000 urinary corticoid analyses have been performed routinely in our laboratory. The method used for this purpose was described in 1950 (Sprechler). We determine the corticoids which can be extracted from the urine with chloroform immediately after acidification to pH 1. The extract is washed with sodium hydroxide and water, a Girard separation is performed, and finally the reducing power of the ketonic fraction is measured by means of the phosphomolybdic acid reagent reaction. During the last few years two other chemical reactions have been used for comparison: The formaldehyde and the Porter-Silber method. After a thorough examination of the above methods a standard technique was followed. In the formaldehyde method a microdiffusion in a Conway unit was used instead of distillation of the formaldehyde following the oxidation with periodic acid. The calibration curve was corrected for loss of material by taking the standard doses of DOC through all the procedures of the method. A micromodification of the Porter-Silber method was chosen. Furthermore attempts were made to determine how specific the chromatographic procedure is in the determination of steroids in urinary extracts. For this purpose the Florisil column was used, and the technique described by Nelson & Samuels was followed. Finally we have investigated the glucuronide-bound corticoids in urine in a smaller series of objects.

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Microbeam analysis. Electron probe microanalysis. Guidelines for determining the carbon content of steels using a calibration curve method

10.3403/30118736u ◽

2015 ◽

Keyword(s):

Carbon Content ◽

Calibration Curve ◽

Electron Probe Microanalysis ◽

Electron Probe ◽

Microbeam Analysis ◽

Curve Method

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Calibration of Radiocarbon Dates for the Late Pleistocene Using U/Th Dates on Stalagmites

Radiocarbon ◽

10.1017/s003382220004087x ◽

1997 ◽

Vol 39 (1) ◽

pp. 27-32 ◽

Cited By ~ 40

Author(s):

John C. Vogel ◽

Joel Kronfeld

Keyword(s):

South Africa ◽

Magnetic Dipole ◽

Satisfactory Agreement ◽

Late Pleistocene ◽

Calibration Curve ◽

Dipole Field ◽

Radiocarbon Dates ◽

The Past ◽

The Earth ◽

Magnetic Dipole Field

Twenty paired 14C and U/Th dates covering most of the past 50,000 yr have been obtained on a stalagmite from the Cango Caves in South Africa as well as some additional age-pairs on two stalagmites from Tasmania that partially fill a gap between 7 ka and 17 ka ago. After allowance is made for the initial apparent 14C ages, the age-pairs between 7 ka and 20 ka show satisfactory agreement with the coral data of Bard et al. (1990, 1993). The results for the Cango stalagmite between 25 ka and 50 ka show the 14C dates to be substantially younger than the U/Th dates except at 49 ka and 29 ka, where near correspondence occurs. The discrepancies may be explained by variations in 14C production caused by changes in the magnetic dipole field of the Earth. A tentative calibration curve for this period is offered.

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A prognostic nomogram based on LASSO Cox regression in patients with alpha-fetoprotein-negative hepatocellular carcinoma following non-surgical therapy

BMC Cancer ◽

10.1186/s12885-021-07916-3 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Dongdong Zhou ◽

Xiaoli Liu ◽

Xinhui Wang ◽

Fengna Yan ◽

Peng Wang ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Surgical Therapy ◽

Calibration Curve ◽

Cox Regression ◽

Validation Cohort ◽

Risk Group ◽

Risk Groups ◽

High Risk Group ◽

Alpha Fetoprotein ◽

Clinicopathologic Characteristics

Abstract Background Alpha-fetoprotein-negative hepatocellular carcinoma (AFP-NHCC) (< 8.78 ng/mL) have special clinicopathologic characteristics and prognosis. The aim of this study was to apply a new method to establish and validate a new model for predicting the prognosis of patients with AFP-NHCC. Methods A total of 410 AFP-negative patients with clinical diagnosed with HCC following non-surgical therapy as a primary cohort; 148 patients with AFP-NHCC following non-surgical therapy as an independent validation cohort. In primary cohort, independent factors for overall survival (OS) by LASSO Cox regression were all contained into the nomogram1; by Forward Stepwise Cox regression were all contained into the nomogram2. Nomograms performance and discriminative power were assessed with concordance index (C-index) values, area under curve (AUC), Calibration curve and decision curve analyses (DCA). The results were validated in the validation cohort. Results The C-index of nomogram1was 0.708 (95%CI: 0.673–0.743), which was superior to nomogram2 (0.706) and traditional modes (0.606–0.629). The AUC of nomogram1 was 0.736 (95%CI: 0.690–0.778). In the validation cohort, the nomogram1 still gave good discrimination (C-index: 0.752, 95%CI: 0.691–0.813; AUC: 0.784, 95%CI: 0.709–0.847). The calibration curve for probability of OS showed good homogeneity between prediction by nomogram1 and actual observation. DCA demonstrated that nomogram1 was clinically useful. Moreover, patients were divided into three distinct risk groups for OS by the nomogram1: low-risk group, middle-risk group and high-risk group, respectively. Conclusions Novel nomogram based on LASSO Cox regression presents more accurate and useful prognostic prediction for patients with AFP-NHCC following non-surgical therapy. This model could help patients with AFP-NHCC following non-surgical therapy facilitate a personalized prognostic evaluation.

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Preoperative prediction for lauren type of gastric cancer: A radiomics nomogram analysis based on CT images and clinical features

Journal of X-Ray Science and Technology ◽

10.3233/xst-210888 ◽

2021 ◽

pp. 1-12

Author(s):

Zongqiong Sun ◽

Linfang Jin ◽

Shuai Zhang ◽

Shaofeng Duan ◽

Wei Xing ◽

...

Keyword(s):

Gastric Cancer ◽

Clinical Features ◽

Calibration Curve ◽

Prediction Models ◽

Ct Images ◽

Clinical Findings ◽

Training Set ◽

Prediction Probability ◽

Radiomics Signature ◽

Testing Set

PURPOSE: To investigate feasibility of predicting Lauren type of gastric cancer based on CT radiomics nomogram before operation. MATERIALS AND METHODS: The clinical data and pre-treatment CT images of 300 gastric cancer patients with Lauren intestinal or diffuse type confirmed by postoperative pathology were retrospectively analyzed, who were randomly divided into training set and testing set with a ratio of 2:1. Clinical features were compared between the two Lauren types in the training set and testing set, respectively. Gastric tumors on CT images were manually segmented using ITK-SNAP software, and radiomic features of the segmented tumors were extracted, filtered and minimized using the least absolute shrinkage and selection operator (LASSO) regression to select optimal features and develop radiomics signature. A nomogram was constructed with radiomic features and clinical characteristics to predict Lauren type of gastric cancer. Clinical model, radiomics signature model, and the nomogram model were compared using the receiver operating characteristic (ROC) curve analysis with area under the curve (AUC). The calibration curve was used to test the agreement between prediction probability and actual clinical findings, and the decision curve was performed to assess the clinical usage of the nomogram model. RESULTS: In clinical features, Lauren type of gastric cancer relate to age and CT-N stage of patients (all p < 0.05). Radiomics signature was developed with the retained 10 radiomic features. The nomogram was constructed with the 2 clinical features and radiomics signature. Among 3 prediction models, performance of the nomogram was the best in predicting Lauren type of gastric cancer, with the respective AUC, accuracy, sensitivity and specificity of 0.864, 78.0%, 90.0%, 70.0%in the testing set. In addition, the calibration curve showed a good agreement between prediction probability and actual clinical findings (p > 0.05). CONCLUSION: The nomogram combining radiomics signature and clinical features is a useful tool with the increased value to predict Lauren type of gastric cancer.

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Assessment of reliability and validity of the 5-scale grading system of the point-of-care immunoassay for tear matrix metalloproteinase-9

Scientific Reports ◽

10.1038/s41598-021-92020-6 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Minjeong Kim ◽

Ja Young Oh ◽

Seon Ha Bae ◽

Seung Hyeun Lee ◽

Won Jun Lee ◽

...

Keyword(s):

Matrix Metalloproteinase ◽

Calibration Curve ◽

Point Of Care ◽

Interobserver Reliability ◽

Intraclass Correlation ◽

Reliability And Validity ◽

Correlation Coefficients ◽

Grading System ◽

Intraclass Correlation Coefficients ◽

The Difference

AbstractWe evaluated the reliability and validity of the 5-scale grading system to interpret the point-of-care immunoassay for tear matrix metalloproteinase (MMP)-9. Six observers graded red bands of photographs of the readout window in MMP-9 immunoassay kit (InflammaDry) two times with 2-week interval based on the 5-scale grading system (i.e. grade 0–4). Interobserver and intraobserver reliability were evaluated using intraclass correlation coefficients. The interobserver agreements were analyzed according to the severity of tear MMP-9 expression. To validate the system, a concentration calibration curve was made using MMP-9 solutions with reference concentrations, then the distribution of MMP-9 concentrations was analyzed according to the 5-scale grading system. Both intraobserver and interobserver reliability was excellent. The readout grades were significantly correlated with the quantified colorimetric densities. The interobserver variance of readout grades had no correlation with the severity of the measured densities. The band density continued to increase up to a maximal concentration (i.e. 5000 ng/mL) according to the calibration curve. The difference of grades reflected the change of MMP-9 concentrations sensitively, especially between grade 2 and 4. Together, our data indicate that the subjective 5-scale grading system in the point-of-care MMP-9 immunoassay is an easy and reliable method with acceptable accuracy.

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The hemocyte counts as a potential biomarker for predicting disease progression in COVID-19: a retrospective study

Clinical Chemistry and Laboratory Medicine (CCLM) ◽

10.1515/cclm-2020-0377 ◽

2020 ◽

Vol 58 (7) ◽

pp. 1106-1115 ◽

Cited By ~ 14

Author(s):

Yufen Zheng ◽

Ying Zhang ◽

Hongbo Chi ◽

Shiyong Chen ◽

Minfei Peng ◽

...

Keyword(s):

Risk Factors ◽

Platelet Count ◽

Disease Progression ◽

Neutrophil Count ◽

Calibration Curve ◽

Lymphocyte Count ◽

Severe Disease ◽

Clinical Impact ◽

Predictive Tool ◽

Potential Biomarker

AbstractObjectivesIn December 2019, there was an outbreak of coronavirus disease 2019 (COVID-19) in Wuhan, China, and since then, the disease has been increasingly spread throughout the world. Unfortunately, the information about early prediction factors for disease progression is relatively limited. Therefore, there is an urgent need to investigate the risk factors of developing severe disease. The objective of the study was to reveal the risk factors of developing severe disease by comparing the differences in the hemocyte count and dynamic profiles in patients with severe and non-severe COVID-19.MethodsIn this retrospectively analyzed cohort, 141 confirmed COVID-19 patients were enrolled in Taizhou Public Health Medical Center, Taizhou Hospital, Zhejiang Province, China, from January 17, 2020 to February 26, 2020. Clinical characteristics and hemocyte counts of severe and non-severe COVID patients were collected. The differences in the hemocyte counts and dynamic profiles in patients with severe and non-severe COVID-19 were compared. Multivariate Cox regression analysis was performed to identify potential biomarkers for predicting disease progression. A concordance index (C-index), calibration curve, decision curve and the clinical impact curve were calculated to assess the predictive accuracy.ResultsThe data showed that the white blood cell count, neutrophil count and platelet count were normal on the day of hospital admission in most COVID-19 patients (87.9%, 85.1% and 88.7%, respectively). A total of 82.8% of severe patients had lymphopenia after the onset of symptoms, and as the disease progressed, there was marked lymphopenia. Multivariate Cox analysis showed that the neutrophil count (hazard ratio [HR] = 4.441, 95% CI = 1.954–10.090, p = 0.000), lymphocyte count (HR = 0.255, 95% CI = 0.097–0.669, p = 0.006) and platelet count (HR = 0.244, 95% CI = 0.111–0.537, p = 0.000) were independent risk factors for disease progression. The C-index (0.821 [95% CI, 0.746–0.896]), calibration curve, decision curve and the clinical impact curve showed that the nomogram can be used to predict the disease progression in COVID-19 patients accurately. In addition, the data involving the neutrophil count, lymphocyte count and platelet count (NLP score) have something to do with improving risk stratification and management of COVID-19 patients.ConclusionsWe designed a clinically predictive tool which is easy to use for assessing the progression risk of COVID-19, and the NLP score could be used to facilitate patient stratification management.

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