Biomarkers geochemistry of the Alpagut oil shale sequence: an evaluation of dispositional environments and source rock potential from Dodurga-Çorum basin (N-Turkey)

The Cenozoic Çankırı-Çorum basin, with sedimentary facies of varying thickness and distribution, contains raw matters such as coal deposits, oil shales and evaporate. Source rock and sedimentary environment characteristics of the oil shale sequence have been evaluated. The studied oil shales have high organic matter content (from 2.97 to 15.14%) and show excellent source rock characteristics. Oil shales are represented by very high hydrogen index (532–892 mg HC/g TOC) and low oxygen index (8–44 mgCO2/g TOC) values. Pyrolysis data indicate that oil shales contain predominantly Type I and little Type II kerogen. The biomarker data reveal the presence of algal, bacterial organic matter and terrestrial organic matter with high lipid content. These findings show that organic matters in the oil shales can generate hydrocarbon, especially oil. High C26/C25, C24/C23 and low C22/C21 tricyclic terpane, C31R/C30 hopane and DBT/P ratios indicate that the studied oil shales were deposited in a lacustrine environment, and very low Pr/Ph ratio is indicative of anoxic character for the depositional environment. Tmax values from the pyrolysis analysis are in the range of 418–443 °C, and production index ranges from 0.01 to 0.08. On the gas chromatography, high Pr/nC17 and Ph/nC18 ratios and CPI values significantly exceeding 1 were determined. Very low 22S/(22S + 22R) homohopane, 20S/(20S + 20R) sterane, diasterane/sterane and Ts/(Ts + Tm) ratios were calculated from the biomarker data. Results of all these analyses indicate that Alpagut oil shales have not yet matured and have not entered the oil generation window.

Supplemental Material: History of earthquakes along the creeping section of the San Andreas fault, California, USA

Supplemental figures related to biomarker analysis, thermal modeling, and experimental setup; more detailed methodology, and tables containing model parameters and biomarker data.<br>

Supplemental Material: History of earthquakes along the creeping section of the San Andreas fault, California, USA

Supplemental figures related to biomarker analysis, thermal modeling, and experimental setup; more detailed methodology, and tables containing model parameters and biomarker data.<br>

Supplemental Material: Two-pronged kill mechanism at the end-Triassic mass extinction

Details of the methodology, biomarker data, Rock-Eval pyrolysis, episodic versus persistent PZE, and full ecological changes relative to biomarker distributions.<br>

Supplemental Material: Two-pronged kill mechanism at the end-Triassic mass extinction

Details of the methodology, biomarker data, Rock-Eval pyrolysis, episodic versus persistent PZE, and full ecological changes relative to biomarker distributions.<br>

A method to estimate probability of disease and vaccine efficacy from clinical trial immunogenicity data

Vaccine efficacy is often assessed by counting disease cases in a clinical trial. A new quantitative framework proposed here (“PoDBAY,” Probability of Disease Bayesian Analysis), estimates vaccine efficacy (and confidence interval) using immune response biomarker data collected shortly after vaccination. Given a biomarker associated with protection, PoDBAY describes the relationship between biomarker and probability of disease as a sigmoid probability of disease (“PoD”) curve. The PoDBAY framework is illustrated using clinical trial simulations and with data for influenza, zoster, and dengue virus vaccines. The simulations demonstrate that PoDBAY efficacy estimation (which integrates the PoD and biomarker data), can be accurate and more precise than the standard (case-count) estimation, contributing to more sensitive and specific decisions than threshold-based correlate of protection or case-count-based methods. For all three vaccine examples, the PoD fit indicates a substantial association between the biomarkers and protection, and efficacy estimated by PoDBAY from relatively little immunogenicity data is predictive of the standard estimate of efficacy, demonstrating how PoDBAY can provide early assessments of vaccine efficacy. Methods like PoDBAY can help accelerate and economize vaccine development using an immunological predictor of protection. For example, in the current effort against the COVID-19 pandemic it might provide information to help prioritize (rank) candidates both earlier in a trial and earlier in development.

Supplemental Material: Putative fossils of chemotrophic microbes preserved in seep carbonates from Vestnesa Ridge, off northwest Svalbard, Norway

Detailed methods, supplemental figures showing microfacies context of microstructures and nanoSIMS data correlation plots, as well as supplemental data file including nanoSIMS data, lipid biomarker data, mineralogy, and carbonate stable carbon and oxygen isotope compositions.<br>

Supplemental Material: Putative fossils of chemotrophic microbes preserved in seep carbonates from Vestnesa Ridge, off northwest Svalbard, Norway

Detailed methods, supplemental figures showing microfacies context of microstructures and nanoSIMS data correlation plots, as well as supplemental data file including nanoSIMS data, lipid biomarker data, mineralogy, and carbonate stable carbon and oxygen isotope compositions.<br>