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Abstract. Iodine (I) abundance in marine carbonates (measured as an elemental ratio with calcium, I / Ca) is of broad interest as a proxy for local/regional ocean redox. This connection arises because the speciation of iodine in seawater, the balance between iodate (IO3-) and iodide (I−), is sensitive to the prevalence of oxic vs. anoxic conditions. However, although I / Ca ratios are increasingly commonly being measured in ancient carbonate samples, a fully quantitative interpretation of this proxy requires the availability of a mechanistic interpretative framework for the marine iodine cycle that can account for the extent and intensity of ocean deoxygenation in the past. Here we present and evaluate a representation of marine iodine cycling embedded in an Earth system model (“cGENIE”) against both modern and paleo-observations. In this framework, we account for IO3- uptake and release of I− through the biological pump, the reduction in ambient IO3- to I− in the water column, and the re-oxidation of I− to IO3-. We develop and test a variety of different plausible mechanisms for iodine reduction and oxidation transformation and contrast model projections against an updated compilation of observed dissolved IO3- and I− concentrations in the present-day ocean. By optimizing the parameters controlling previously proposed mechanisms involved in marine iodine cycling, we find that we can obtain broad matches to observed iodine speciation gradients in zonal surface distribution, depth profiles, and oxygen-deficient zones (ODZs). However, we also identify alternative, equally well performing mechanisms which assume a more explicit mechanistic link between iodine transformation and environment – an ambiguity that highlights the need for more process-based studies on modern marine iodine cycling. Finally, to help distinguish between competing representations of the marine iodine cycle and because our ultimate motivation is to further our ability to reconstruct ocean oxygenation in the geological past, we conducted “plausibility tests” of different model schemes against available I / Ca measurements made on Cretaceous carbonates – a time of substantially depleted ocean oxygen availability compared to modern and hence a strong test of our model. Overall, the simultaneous broad match we can achieve between modeled iodine speciation and modern observations, and between forward proxy modeled I / Ca and geological elemental ratios, supports the application of our Earth system modeling in simulating the marine iodine cycle to help interpret and constrain the redox evolution of past oceans. 

Deep learning-based virtual staining was developed to introduce image contrast to label-free tissue sections, digitally matching the histological staining, which is time-consuming, labor-intensive, and destructive to tissue. Standard virtual staining requires high autofocusing precision during the whole slide imaging of label-free tissue, which consumes a significant portion of the total imaging time and can lead to tissue photodamage. Here, we introduce a fast virtual staining framework that can stain defocused autofluorescence images of unlabeled tissue, achieving equivalent performance to virtual staining of in-focus label-free images, also saving significant imaging time by lowering the microscope’s autofocusing precision. This framework incorporates a virtual autofocusing neural network to digitally refocus the defocused images and then transforms the refocused images into virtually stained images using a successive network. These cascaded networks form a collaborative inference scheme: the virtual staining model regularizes the virtual autofocusing network through a style loss during the training. To demonstrate the efficacy of this framework, we trained and blindly tested these networks using human lung tissue. Using 4× fewer focus points with 2× lower focusing precision, we successfully transformed the coarsely-focused autofluorescence images into high-quality virtually stained H&E images, matching the standard virtual staining framework that used finely-focused autofluorescence input images. Without sacrificing the staining quality, this framework decreases the total image acquisition time needed for virtual staining of a label-free whole-slide image (WSI) by ~32%, together with a ~89% decrease in the autofocusing time, and has the potential to eliminate the laborious and costly histochemical staining process in pathology. 

Abstract The Early Mississippian (Tournaisian) positive δ13C excursion (mid-Tournaisian carbon isotope excursion [TICE]) was one of the largest in the Phanerozoic, and the organic carbon (OC) burial associated with its development is hypothesized to have enhanced late Paleozoic cooling and glaciation. We tested the hypothesis that expanded ocean anoxia drove widespread OC burial using uranium isotopes (δ238U) of Lower Mississippian marine limestone as a global seawater redox proxy. The δ238U trends record a large Tournaisian negative excursion lasting ∼1 m.y. The lack of covariation between δ238U values and facies changes and proxies for local depositional and diagenetic influences suggests that the δ238U trends represent a global seawater redox signal. The negative δ238U excursion is coincident with the first TICE positive excursion, supporting the hypothesis that an expanded ocean anoxic event controlled OC burial. These results provide the first evidence from a global seawater redox proxy that an ocean anoxic event drove Tournaisian OC burial and controlled Early Mississippian cooling and glaciation. Uranium and carbon modeling results indicate that (1) there was an ∼6× increase in euxinic seafloor area, (2) OC burial was initially driven by expanded euxinia followed by expanded anoxic/suboxic conditions, and (3) OC burial mass was ∼4–17× larger than that sequestered during other major ocean anoxic events.