To address thermal processes involving carbonate rocks, we measured thermal diffusivity (D) of a suite of carbonate minerals and rocks using laser flash analysis at temperatures from ~300 K up to ~1000 K. For different minerals, D was governed by density or unit cell size. Near room temperature, for example, D ranged from 4.36 mm 2 s -1 for magnesite to 1.61 mm 2 s -1 for calcite. At any given temperature, D decreases from magnesite to dolomite to rhodochrosite to calcite. As temperature increases, D decreases for all samples, with the strongest drop occurring in the interval ~300-500 K. For rocks, mineralogy and porosity were also strong controls on rock D. Calcitic limestones showed proportionally lower D than the mineral, scaling with measured pore fraction, whereas dolomitized rocks produced higher D than calcitic rocks across the interval 300-600 K. Measurements of heat capacity and density were used to calculate thermal conductivity (k) for the suite, and these results show a stronger temperature dependence for k of carbonate rocks and minerals than previous studies, with k decreasing by ~50% between ambient and ~600 K.These results can strongly affect models of the geothermal gradient. Because dolomite conducts heat more efficiently across all measured temperatures than calcite, regions with large proportions of dolomitized rocks may have lower temperatures at depth than those dominated by calcitic carbonates. Additionally, the strong temperature dependence of carbonate rocks introduces the potential for feedback relationships in high heat-producing or thin crust, suggesting that carbonate-dominated crust could have higher temperatures at depth than previously thought. This strong temperature dependence also has implications for the duration of metamorphic events such as metasomatism driving skarn mineralization, or contact metamorphism resulting from intrusion of an igneous body.

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Thermal conductivity (K) describes the response of matter to temporal or spatial variations in temperature (T). To quantify the effect of varying mineralogy on heat transport of rocks, an accurate (±2%) contact-free heat transfer method was applied at ambient T to multiple sections from 33 different low porosity, continental, igneous and metamorphic rocks. Thermal diffusivity (Dheat) was measured using laser-flash analysis, which was previously used to construct our large mineralogical database and which mitigates spurious radiative transfer found in other techniques. These measurements constrain K, because K is the product of Dheat with the known (or calculable) properties of density and specific heat measured at constant pressure (P). Compositions, proportions, and orientations of minerals, plus rock density, average grain-size (L), and porosity were characterized for 61 sections from 29 silicate rocks plus 5 sections from 3 marbles. Our database was used to evaluate component summation (averaging) formulae that were recently developed by considering Fourier’s laws, and to quantify the dependence of K and/or Dheat on key rock descriptors. We found that: (1) phase proportions and compositions are the main cause of variations; (2) minor porosity and foliation have minor effects; and (3) within ~5%, isotropic rocks follow Dheat = ½{[Σ(fi/Di)]-1+Σ(fiDi)} where fi is volumetric mineral fraction, analogous to the Voigt-Reuss-Hill average for elastic moduli. Using this formula predictively depends on the accuracy of fi and Di. Quartzo-feldspathic rocks can be described by a new formula that uses only quartz fraction and plagioclase composition. Combining our mineralogical model with a universal formula for Dheat(T) and a thermodynamic identity for K(P) accurately constrains conductive thermal transport for Earth’s low porosity, crystalline rock layers.

Recent advances in cancer immuno-therapeutics such as checkpoint inhibitors, chimeric antigen-receptor T cells, and tumor infiltrating T cells (TIL) are now significantly impacting cancer patients in a positive manner. Although very promising, reports indicate no more than 25% of cases result in complete remission. One of the limitations of these treatments is the identity of putative cancer antigens in each patient, as it is technically challenging to identify cancer antigens in a rapid fashion. Thus, identification of cancer antigens followed by targeted treatment will increase the efficacy of cancer immunotherapies. To achieve this goal, a combined technologies platform of deep genomic sequencing and personalized immune assessment was devised, termed Genomics Driven Immunoproteomics (GDI). Using this technological platform, we report the discovery of 149 tumor antigens from human breast cancer patients. Significant number of these putative cancer antigens arise from single nucleotide variants (SNVs), as well as insertions and deletions that results into frame-shift mutations. We propose a general model of anti-cancer immunity and suggest that the GDI platform may help identify patient-specific tumor antigens in a timely fashion for precision immunotherapies.

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