This study was designed to evaluate the value of contrast-enhanced whole-heart coronary MRA (CMRA) at 3.0T in depicting the cardiac venous anatomy. In cardiac resynchronization therapy (CRT), left ventricular (LV) pacing is achieved by positioning the LV lead in one of the tributaries of the coronary sinus (CS). Pre-implantation knowledge of the venous anatomy may help determine whether transvenous LV lead placement for CRT is feasible. Images of 51 subjects undergoing contrast-enhanced whole-heart CMRA at 3.0T were retrospectively analyzed. Data acquisition was performed using electrocardiography-triggered, navigator-gated, inversion-recovery prepared, segmented gradient-echo sequence. A 32-element cardiac coil was used for data acquisition. The visibility of the cardiac veins was graded visually using a 4-point scale (1: poor-4: excellent). The paired Student t test was used to evaluate differences in diameters of the ostium of the CS in anteroposterior and superoinferior direction. The cardiac veins were finally evaluated in 48 subjects with three anatomic variations. The diameter of the CS ostium in the superoinferior direction (1.13 ± 0.26 cm) was larger than in the anteroposterior direction (0.82 ± 0.19 cm) (P < 0.05). The mean visibility score of CS, posterior interventricular vein, posterior vein of the left ventricle, left marginal vein, and anterior interventricular vein was 4.0 ± 0.0, 3.4 ± 0.5, 3.4 ± 0.5, 3.0 ± 0.8, and 3.3 ± 0.5, respectively. In conclusion, contrast-enhanced whole-heart CMRA at 3.0T can depict the normal and variant cardiac venous anatomy.

Models test our understanding of processes and can reach beyond the spatial and temporal scales of measurements. Multi-component Reactive Transport Models (RTMs), initially developed more than three decades ago, have been used extensively to explore the interactions of geothermal, hydrologic, geochemical, and geobiological processes in subsurface systems. Driven by extensive data sets now available from intensive measurement efforts, there is a pressing need to couple RTMs with other community models to explore non-linear interactions among the atmosphere, hydrosphere, biosphere, and geosphere. Here we briefly review the history of RTM development, summarize the current state of RTM approaches, and identify new research directions, opportunities, and infrastructure needs to broaden the use of RTMs. In particular, we envision the expanded use of RTMs in advancing process understanding in the Critical Zone, the veneer of the Earth that extends from the top of vegetation to the bottom of groundwater. We argue that, although parsimonious models are essential at larger scales, process-based models offer tools to explore the highly nonlinear coupling that characterizes natural systems. We present seven testable hypotheses that emphasize the unique capabilities of process-based RTMs for (1) elucidating chemical weathering and its physical and biogeochemical drivers; (2) understanding the interactions among roots, micro-organisms, carbon, water, and minerals in the rhizosphere; (3) assessing the effects of heterogeneity across spatial and temporal scales; and (4) integrating the vast quantity of novel data, including “omics” data (genomics, transcriptomics, proteomics, metabolomics), elemental concentration and speciation data, and isotope data into our understanding of complex earth surface systems. With strong support from data-driven sciences, we are now in an exciting era where integration of RTM framework into other community models will facilitate process understanding across disciplines and across scales.

Data sharing benefits the researcher, the scientific community, and the public by allowing the impact of data to be generalized beyond one project and by making science more transparent. However, many scientific communities have not developed protocols or standards for publishing, citing, and versioning datasets. One community that lags in data management is that of low-temperature geochemistry (LTG). This paper resulted from an initiative from 2018 through 2020 to convene LTG and data scientists in the U.S. to strategize future management of LTG data. Through webinars, a workshop, a preprint, a townhall, and a community survey, the group of U.S. scientists discussed the landscape of data management for LTG – the data-scape. Currently this data-scape includes a “street bazaar” of data repositories. This was deemed appropriate in the same way that LTG scientists publish articles in many journals. The variety of data repositories and journals reflect that LTG scientists target many different scientific questions, produce data with extremely different structures and volumes, and utilize copious and complex metadata. Nonetheless, the group agreed that publication of LTG science must be accompanied by sharing of data in publicly accessible repositories, and, for sample-based data, registration of samples with globally unique persistent identifiers. LTG scientists should use certified data repositories that are either highly structured databases designed for specialized types of data, or unstructured generalized data systems. Recognizing the need for tools to enable search and cross-referencing across the proliferating data repositories, the group proposed that the overall data informatics paradigm in LTG should shift from “build data repository, data will come” to “publish data online, cybertools will find”. Funding agencies could also provide portals for LTG scientists to register funded projects and datasets, and forge approaches that cross national boundaries. The needed transformation of the LTG data culture requires emphasis in student education on science and management of data.