Identifying pathfinder elements for gold in bulk-rock geochemical data from the Cripple Creek Au–Te deposit: a statistical approach

The Cripple Creek alkaline igneous rock-related, low-sulfidation epithermal gold telluride deposit, Colorado, is hosted in the 10 km wide Oligocene alkaline volcanic Cripple Creek diatreme in Proterozoic rocks. Gold occurs as native gold, Au-tellurides, and in the structure of arsenian pyrite, in potassically altered high-grade veins, and as disseminations in the host rocks.Correlation coefficients, principal component analysis, hierarchical cluster analysis and random forests were used to analyse major and trace element compositions of 995 rock samples primarily from low-grade gold mineralization in drill core from three currently operating pits (Wild Horse Extension, Globe Hill and Schist Island) in the northwestern part of the Cripple Creek diatreme. These methods suggest that Ag, As, Bi, Te and W are the best pathfinders to gold mineralization in low-grade disseminated ore. Although Mo correlates with gold in other studies and is spatially related to gold veins, molybdenite post-dated the formation of gold and is likely related to a late-stage porphyry overprint. These elements, in conjunction with mineralogical studies, indicate that tellurides, fluorite, quartz, carbonates, roscoelite, tennantite-tetrahedrite, pyrite, sphalerite, muscovite, monazite, bastnäsite and hübnerite serve as exploration guides to ore.

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Chapter 17: Epithermal Gold Deposits Related to Alkaline Igneous Rocks in the Cripple Creek District, Colorado, United States

10.5382/sp.23.17 ◽

2020 ◽

pp. 355-373

Author(s):

Karen D. Kelley ◽

Eric P. Jensen ◽

Jason S. Rampe ◽

Doug White

Keyword(s):

Gold Mineralization ◽

Fracture Network ◽

Hydrothermal Activity ◽

Gold Deposits ◽

Igneous Rocks ◽

Low Grade ◽

Key Factors ◽

Enriched Mantle ◽

Cripple Creek ◽

History Of

Abstract Cripple Creek is among the largest epithermal districts in the world, with more than 800 metric tons (t) Au (>26.4 Moz). The ores are associated spatially, temporally, and genetically with ~34 to 28 Ma alkaline igneous rocks that were emplaced into an 18-km2 diatreme complex and surrounding Proterozoic rocks. Gold occurs in high-grade veins, as bulk tonnage relatively low-grade ores, and in hydrothermal breccias. Pervasive alteration in the form of potassic metasomatism is extensive and is intimately associated with gold mineralization. Based on dating of intrusions and molybdenite and gangue minerals (primarily using 40Ar/39Ar and Re-Os techniques), the region experienced a protracted but intermittent history of magmatism (over a period of at least 5 m.y.) and hydrothermal activity (intermittent over the final ~3 m.y. of magmatic activity). Key factors that likely played a role in the size and grade of the deposit were (1) the generation of alkaline magmas during a transition between subduction and extension that tapped a chemically enriched mantle source; (2) a long history of structural preparation, beginning in the Proterozoic, which created deep-seated structures to allow the magmas and ore fluids to reach shallow levels in the crust, and which produced a fracture network that increased permeability; and (3) an efficient hydrothermal system, including effective gold transport mechanisms, and multiple over-printed hydrothermal events.

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Chemometrics as a Tool in the Study of Lead Toxicity in Rats

Journal of the Mexican Chemical Society ◽

10.29356/jmcs.v59i1.7 ◽

2017 ◽

Vol 59 (1) ◽

Author(s):

Judith Amador-Hernández

Keyword(s):

Biochemical Parameters ◽

Pearson Correlation ◽

Correlation Coefficients ◽

Lead Toxicity ◽

Principal Component ◽

Hierarchical Cluster ◽

Glutathione S Transferase ◽

Control Groups ◽

Kidney Weight ◽

Procrustean Analysis

<p>In this work, chemometric tools were applied to establish correlations between biomarkers and to identify the most significant ones in relation to acute exposure of Wistar rats to Pb. The metal content in biological matrices (serum, urine, liver, brain, and kidney), biochemical parameters (protein content, activity of the Glutathione S–Transferase enzymes, and urinalysis), apart from morphological measurements of organisms, were estimated in both the exposed and the control groups and submitted to Significance tests, Principal Component Analysis, Hierarchical Cluster Analysis, and Generalized Procrustean Analysis. It could be observed that Pb in serum, but not in erythrocytes, was the biomarker associated with the Pb content in kidney and other parameters related to this organ. In the same way, Pearson correlation coefficients emphasized the relation between Pb in serum and these variables, with the exception of kidney weight. Additionally, Pb in serum was found to be the biomarker with the greatest difference between the control and the exposed groups, which converts it into the most sensitive biomarker in the present study. </p>

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Analytical Method Development and Chemometric Approach for Evidencing Presence of Plasticizer Residues in Nectar Honey Samples

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph17051692 ◽

2020 ◽

Vol 17 (5) ◽

pp. 1692 ◽

Cited By ~ 4

Author(s):

Ivan Notardonato ◽

Sergio Passarella ◽

Giuseppe Ianiri ◽

Cristina Di Fiore ◽

Mario Vincenzo Russo ◽

...

Keyword(s):

Analytical Method ◽

Method Development ◽

Correlation Coefficients ◽

Principal Component ◽

Hierarchical Cluster ◽

Anthropogenic Sources ◽

Mass Spectrometry Analysis ◽

Chemical Contamination ◽

Spectrometry Analysis ◽

Chemometric Approach

Over the years, anthropogenic sources have increasingly affected food quality. One of the most sensitive and nutritional matrices affected by chemical contamination is honey, due to the use of acaricides. Recently, the attention has moved to the presence of phthalates (PAEs) and bisphenol A (BP-A), molecules present in plastic materials used both in the production phase and in the conservation of honey. In this study, an analytical method for the simultaneous determination of PAEs (dimethyl phthalate DMP, diethyl phthalate DEP, diisobutyl phthalate DiBP, dibutyl phthalate DBP, bis(2-ethylhexyl) phthalate DEHP, and di-n-octyl-phthalate DnOP) and BP-A was developed. The extraction technique is the ultrasound-vortex-assisted dispersive liquid–liquid microextraction (UVA-DLLME), using 150 µL of toluene as an extraction solvent, followed by the gas chromatography coupled with ion trap mass spectrometry analysis (GC–IT/MS). The developed method is sensitive, reliable, and reproducible: it shows high correlation coefficients (R > 0.999); limits of detection (LODs) less than 11 ng·g−1; limits of quantification (LOQs) less than 16 ng·g−1; repeatability below 3.6%, except BP-A (11.6%); and accuracy below 4.8%, except BP-A (17.6%). The method was applied to 47 nectar honey samples for evidencing similarities among them. The chemometric approach based on Hierarchical Cluster Analysis and Principal Component Analysis evidenced some similitudes about sample origin as well as marked differences between PAE and BP-A sources.

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FTIR Spectroscopic Imaging Supports Urine Cytology for Classification of Low- and High-Grade Bladder Carcinoma

Cancers ◽

10.3390/cancers13225734 ◽

2021 ◽

Vol 13 (22) ◽

pp. 5734

Author(s):

Monika Kujdowicz ◽

Brygida Mech ◽

Karolina Chrabaszcz ◽

Piotr Chlosta ◽

Krzysztof Okon ◽

...

Keyword(s):

Principal Component ◽

High Sensitivity ◽

Hierarchical Cluster ◽

Cell Types ◽

Diagnostic Methods ◽

Cellular Heterogeneity ◽

Unsupervised Hierarchical Cluster ◽

Molecular Heterogeneity ◽

Low Grade ◽

High Grade

Bladder urothelial carcinoma (BC) is a common, recurrent, life-threatening, and unpredictable disease which is difficult to diagnose. These features make it one of the costliest malignancies. Although many possible diagnostic methods are available, molecular heterogeneity and difficulties in cytological or histological examination induce an urgent need to improve diagnostic techniques. Herein, we applied Fourier transform infrared spectroscopy in imaging mode (FTIR) to investigate patients’ cytology samples assigned to normal (N), low-grade (LG) and high-grade (HG) BC. With unsupervised hierarchical cluster analysis (UHCA) and hematoxylin-eosin (HE) staining, we observed a correlation between N cell types and morphology. High-glycogen superficial (umbrella) and low-glycogen piriform urothelial cells, both with normal morphology, were observed. Based on the spectra derived from UHCA, principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were performed, indicating a variation of protein content between the patient groups. Moreover, BC spectral cytology identified a low number of high-glycogen cells for which a shift of the carbohydrate/phosphate bands was also observed. Despite high cellular heterogeneity, PLS-DA was able to classify the spectra obtained. The voided urine FTIR cytology is one of the options that might be helpful in BC diagnosis, as high sensitivity and specificity up to 97% were determined.

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Characterization of Origin and Evolution of Formation Water in Buried Hill of Jizhong Depression, China, Using Multivariate Statistical Analysis of Geochemical Data

Geofluids ◽

10.1155/2017/5290686 ◽

2017 ◽

Vol 2017 ◽

pp. 1-15 ◽

Cited By ~ 6

Author(s):

Fei Li ◽

Jianhui Zeng

Keyword(s):

Principal Component ◽

Hierarchical Cluster ◽

Geochemical Data ◽

Atmospheric Water ◽

Rock Interaction ◽

Discharge Area ◽

Origin And Evolution ◽

Evaporation Concentration ◽

Jizhong Depression ◽

Buried Hill

Groundwater samples from buried hill of Jizhong Depression were evaluated using two statistical analyses: hierarchical cluster analysis (HCA) and principal component analysis (PCA). The samples were classified into four clusters, C1–C4, in HCA and the hydrochemical types of C1–C4 are HCO3-Na, Cl·HCO3-Na, Cl-Na, and Cl-Na·Ca. From C1 to C2, C3, and C4, the water-rock interaction becomes increasingly intensive, and rNa/rCl gets lower while total dissolved solids and r(Cl-Na)/rMg get higher. Three components of PCA explain 86.87% of the variance. Component1 (PC1), characterized by highly positive loadings in Na+ and Cl−, is related to evaporation concentration. Component2 (PC2) is defined by highly positive loading in HCO3- and is related to influence of atmospheric water. With high positive loadings in Ca2+ and high negative loadings in Na+ and SO42-, component3 (PC3) suggests plagioclase albitization. The combination of HCA and PCA within the hydrogeological contexts allowed the division of study area into five dynamic areas. From recharge area to discharge area, the influence of atmospheric water gets weaker and water-rock interactions such as evaporation concentration and plagioclase albitization become intensive. Therefore groundwater in buried hill showed paths of hydrochemical evolution, from C1, to C2, C3, and C4. Buried hill reservoir in Jizhong Depression is mainly distributed in hydrodynamic blocking and discharge area; therefore the two regions can be the favorable areas for petroleum migration.

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Chemometric Analysis for the Classification of some Groups of Drugs with Divergent Pharmacological Activity on the Basis of some Chromatographic and Molecular Modeling Parameters

Combinatorial Chemistry & High Throughput Screening ◽

10.2174/1386207321666180129102149 ◽

2018 ◽

Vol 21 (2) ◽

pp. 125-137

Author(s):

Jolanta Stasiak ◽

Marcin Koba ◽

Marcin Gackowski ◽

Tomasz Baczek

Keyword(s):

Correlation Analysis ◽

Pharmacological Activity ◽

Correlation Coefficients ◽

Principal Component ◽

Cardiovascular Drugs ◽

New Drugs ◽

Analgesic Drugs ◽

Starting Point ◽

Chromatographic Parameters

Aim and Objective: In this study, chemometric methods as correlation analysis, cluster analysis (CA), principal component analysis (PCA), and factor analysis (FA) have been used to reduce the number of chromatographic parameters (logk/logkw) and various (e.g., 0D, 1D, 2D, 3D) structural descriptors for three different groups of drugs, such as 12 analgesic drugs, 11 cardiovascular drugs and 36 “other” compounds and especially to choose the most important data of them. Material and Methods: All chemometric analyses have been carried out, graphically presented and also discussed for each group of drugs. At first, compounds’ structural and chromatographic parameters were correlated. The best results of correlation analysis were as follows: correlation coefficients like R = 0.93, R = 0.88, R = 0.91 for cardiac medications, analgesic drugs, and 36 “other” compounds, respectively. Next, part of molecular and HPLC experimental data from each group of drugs were submitted to FA/PCA and CA techniques. Results: Almost all results obtained by FA or PCA, and total data variance, from all analyzed parameters (experimental and calculated) were explained by first two/three factors: 84.28%, 76.38 %, 69.71% for cardiovascular drugs, for analgesic drugs and for 36 “other” compounds, respectively. Compounds clustering by CA method had similar characteristic as those obtained by FA/PCA. In our paper, statistical classification of mentioned drugs performed has been widely characterized and discussed in case of their molecular structure and pharmacological activity. Conclusion: Proposed QSAR strategy of reduced number of parameters could be useful starting point for further statistical analysis as well as support for designing new drugs and predicting their possible activity.

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Quality evaluation of tugaksheeree samples by ATR-FTIR spectroscopy using multicomponent analysis

The Natural Products Journal ◽

10.2174/2210315510999200408125555 ◽

2020 ◽

Vol 10 ◽

Cited By ~ 1

Author(s):

Nikunj D. Patel ◽

Niranjan S. Kanaki

Keyword(s):

Principal Component Analysis ◽

Cluster Analysis ◽

Quality Evaluation ◽

Principal Component ◽

Hierarchical Cluster ◽

Attenuated Total Reflectance ◽

Chemometric Methods ◽

Total Reflectance ◽

Fingerprint Region ◽

Ftir Technique

Background: Numerous Ayurvedic formulations contains tugaksheeree as key ingredient. Tugaksheereeis the starch gained from the rhizomes of two plants, Curcuma angustifoliaRoxb. (Zingiberaceae) and Marantaarundinacea (MA) Linn. (Marantaceae). Objective: The primary concerns in quality assessment of Tugaksheeree occur due to adulteration or substitution. Method: In current study, Fourier transform infrared (FTIR) technique with attenuated total reflectance (ATR) facility was used to evaluate tugaksheeree samples. Total 10 different samples were studied and transmittance mode was kept to record the spectra devoid of pellets of KBR. Further treatment was given with multi component tools by considering fingerprint region of the spectra. Multivariate analysis was performed by various chemometric methods. Result: Multi component methods like Principal Component Analysis (PCA), and Hierarchical Cluster Analysis (HCA)were used to discriminate the tugaksheeree samples using Minitab software. Conclusion: This method can be used as a tool to differentiate samples of tugaksheeree from its adulterants and substitutes.

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Multivariate Statistical Approach for Nephrines in Women with Obesity

Molecules ◽

10.3390/molecules26051393 ◽

2021 ◽

Vol 26 (5) ◽

pp. 1393

Author(s):

Ralitsa Robeva ◽

Miroslava Nedyalkova ◽

Georgi Kirilov ◽

Atanaska Elenkova ◽

Sabina Zacharieva ◽

...

Keyword(s):

Type 2 Diabetes ◽

Metabolic Syndrome ◽

Data Analysis ◽

Stress Response ◽

Exploratory Data Analysis ◽

Principal Component ◽

Hierarchical Cluster ◽

Obese Women ◽

Exploratory Data

Catecholamines are physiological regulators of carbohydrate and lipid metabolism during stress, but their chronic influence on metabolic changes in obese patients is still not clarified. The present study aimed to establish the associations between the catecholamine metabolites and metabolic syndrome (MS) components in obese women as well as to reveal the possible hidden subgroups of patients through hierarchical cluster analysis and principal component analysis. The 24-h urine excretion of metanephrine and normetanephrine was investigated in 150 obese women (54 non diabetic without MS, 70 non-diabetic with MS and 26 with type 2 diabetes). The interrelations between carbohydrate disturbances, metabolic syndrome components and stress response hormones were studied. Exploratory data analysis was used to determine different patterns of similarities among the patients. Normetanephrine concentrations were significantly increased in postmenopausal patients and in women with morbid obesity, type 2 diabetes, and hypertension but not with prediabetes. Both metanephrine and normetanephrine levels were positively associated with glucose concentrations one hour after glucose load irrespectively of the insulin levels. The exploratory data analysis showed different risk subgroups among the investigated obese women. The development of predictive tools that include not only traditional metabolic risk factors, but also markers of stress response systems might help for specific risk estimation in obesity patients.

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Spectroscopy as a useful tool for the identification of changes with time in post-mortem vitreous humor for forensic toxicology purposes

Monatshefte für Chemie - Chemical Monthly ◽

10.1007/s00706-021-02786-8 ◽

2021 ◽

Author(s):

Anna Wójtowicz ◽

Agata Mitura ◽

Renata Wietecha-Posłuszny ◽

Rafał Kurczab ◽

Marcin Zawadzki

Keyword(s):

Ir Spectra ◽

Forensic Toxicology ◽

Principal Component ◽

Hierarchical Cluster ◽

Vitreous Humor ◽

Attenuated Total Reflection ◽

Glass Slides ◽

Added Benefit ◽

Ft Ir ◽

Non Destructive

AbstractVitreous humor (VH) is an alternative biological matrix with a great advantage of longer availability for analysis due to the lack of many enzymes. The use of VH in forensic toxicology may have an added benefit, however, this application requires rapid, simple, non-destructive, and relatively portable analytical analysis methods. These requirements may be met by Fourier transform infrared spectroscopy technique (FT-IR) equipped with attenuated total reflection accessory (ATR). FT-IR spectra of vitreous humor samples, deposited on glass slides, were collected and subsequent chemometric data analysis by means of Hierarchical Cluster Analysis and Principal Component Analysis was conducted. Differences between animal and human VH samples and human VH samples stored for diverse periods of time were detected. A kinetic study of changes in the VH composition up to 2 weeks showed the distinction of FT-IR spectra collected on the 1st and 14th day of storage. In addition, data obtained for the most recent human vitreous humor samples—collected 3 and 2 years before the study, presented successful discrimination of all time points studied. The method introduced was unable to detect mephedrone addition to VH in the concentration of 10 µg/cm3. Graphic abstract

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A Methodology Based on FT-IR Data Combined with Random Forest Model to Generate Spectralprints for the Characterization of High-Quality Vinegars

Foods ◽

10.3390/foods10061411 ◽

2021 ◽

Vol 10 (6) ◽

pp. 1411

Author(s):

José Luis P. Calle ◽

Marta Ferreiro-González ◽

Ana Ruiz-Rodríguez ◽

Gerardo F. Barbero ◽

José Á. Álvarez ◽

...

Keyword(s):

Random Forest ◽

Raw Materials ◽

Principal Component ◽

Hierarchical Cluster ◽

Raw Material ◽

Support Vector ◽

Protected Designation Of Origin ◽

Ft Ir

Sherry wine vinegar is a Spanish gourmet product under Protected Designation of Origin (PDO). Before a vinegar can be labeled as Sherry vinegar, the product must meet certain requirements as established by its PDO, which, in this case, means that it has been produced following the traditional solera and criadera ageing system. The quality of the vinegar is determined by many factors such as the raw material, the acetification process or the aging system. For this reason, mainly producers, but also consumers, would benefit from the employment of effective analytical tools that allow precisely determining the origin and quality of vinegar. In the present study, a total of 48 Sherry vinegar samples manufactured from three different starting wines (Palomino Fino, Moscatel, and Pedro Ximénez wine) were analyzed by Fourier-transform infrared (FT-IR) spectroscopy. The spectroscopic data were combined with unsupervised exploratory techniques such as hierarchical cluster analysis (HCA) and principal component analysis (PCA), as well as other nonparametric supervised techniques, namely, support vector machine (SVM) and random forest (RF), for the characterization of the samples. The HCA and PCA results present a clear grouping trend of the vinegar samples according to their raw materials. SVM in combination with leave-one-out cross-validation (LOOCV) successfully classified 100% of the samples, according to the type of wine used for their production. The RF method allowed selecting the most important variables to develop the characteristic fingerprint (“spectralprint”) of the vinegar samples according to their starting wine. Furthermore, the RF model reached 100% accuracy for both LOOCV and out-of-bag (OOB) sets.

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