Simulated nitrous oxide emissions from multiple agroecosystems in the U.S. Corn Belt using the modified SWAT-C model.

Agriculture is a major source of nitrous oxide (N2O) emissions into the atmosphere. However, assessing the impacts of agricultural conservation practices, land use change, and climate adaptation measures on N2O emissions at a large scale is a challenge for process-based model applications. Here, we integrated six N2O emission algorithms for the nitrification processes and seven N2O emission algorithms for the denitrification process into the Soil and Water Assessment Tool-Carbon (SWAT-C). We evaluated the different combinations of methods in simulating N2O emissions under corn (Zea mays L.) production systems with various conservation practices, including fertilization, tillage, and crop rotation (represented by 14 experimental treatments and 83 treatment-years) at five experimental sites across the U.S. Midwest. The SWAT-C model exhibited wide variability in simulating daily average N2O emissions across treatment-years with different method configurations, as indicated by the ranges of R2, NSE, and BIAS (0.04-0.68, -1.78-0.60, and -0.94-0.001, respectively). Our results indicate that the denitrification process has a stronger impact on N2O emissions than the nitrification process. The best performing N2O emission algorithms are those rooted in the CENTURY model, which considers soil pH and respiration effects that were overlooked by other algorithms. The optimal N2O emission algorithm explained about 63% of the variability of annual average N2O emissions, with NSE and BIAS of 0.60 and -0.033, respectively. The model can reasonably represent the impacts of agricultural conservation practices on N2O emissions. We anticipate that the improved SWAT-C model, with its flexible configurations and robust modeling and assessment capabilities, will provide a valuable tool for studying and managing N2O emissions from agroecosystems.

Nitrate losses and nitrous oxide emissions under contrasting tillage and cover crop management.

Agroecosystems in the upper Mississippi River Basin are highly productive but often contribute to deterioration of water quality and greenhouse gas emissions. Cover cropping and no-till are conservation strategies implemented to reduce the environmental impact of these agroecosystems. However, using multiple strategies can lead to systemwide interactions that are not fully understood. These interactions can affect not only environmental quality metrics, such as subsurface drainage nitrate losses or nitrous oxide (N2 O) emissions, but also may influence crop production potential. A field trial was initiated comparing nitrate losses, N2 O emissions, and crop production under systems with fall chisel plow tillage, fall chisel plow tillage with an oat (Avena sativa L.) cover crop (CP-oat), no-till (NT), no-till with a rye (Secale cereale L.) cover crop (NT-rye), and NT with zero N fertilizer. Pathways for nitrate losses and N2 O emissions did not appear linked and were not tied to cover crop or tillage practices. Nitrate losses were linked with drainage volumes, and cover crops and tillage had limited effect on cumulative drainage volumes. Notably, NT-rye altered the relationship between drainage volume and nitrate losses by reducing nitrate concentrations, lowering nitrate losses by 59 ±9% compared with CP-oat and 67 ± 9% compared with NT. Neither cover crop nor tillage consistently affected N2 O emissions or crop yield. Rather, N2 O emissions were closely tied with fertilizer N application and seasonal weather patterns. These findings indicate that nitrate leaching and N2 O emissions are regulated by separate mechanisms, so conservation management may require stacking multiple practices to be effective.

Both subsurface nitrate losses and nitrous oxide emissions were linked with weather. Subsurface nitrate losses were linked with cumulative annual drainage. Nitrous oxide emissions were linked with fertilizer N applications. Rye cover crop with no-till reduced nitrate losses with no yield declines.

COVID-19 Disease, Women's Predominant Non-Heparin Vaccine-Induced Thrombotic Thrombocytopenia and Kounis Syndrome: A Passepartout Cytokine Storm Interplay.

Coronavirus disease 2019 (COVID-19) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) constitute one of the deadliest pandemics in modern history demonstrating cardiovascular, gastrointestinal, hematologic, mucocutaneous, respiratory, neurological, renal and testicular manifestations and further complications. COVID-19-induced excessive immune response accompanied with uncontrolled release of cytokines culminating in cytokine storm seem to be the common pathogenetic mechanism of these complications. The aim of this narrative review is to elucidate the relation between anaphylaxis associated with profound hypotension or hypoxemia with pro-inflammatory cytokine release. COVID-19 relation with Kounis syndrome and post-COVID-19 vaccination correlation with heparin-induced thrombocytopenia with thrombosis (HITT), especially serious cerebral venous sinus thrombosis, were also reviewed. METHODS: A current literature search in PubMed, Embase and Google databases was performed to reveal the pathophysiology, prevalence, clinical manifestation, correlation and treatment of COVID-19, anaphylaxis with profuse hypotension, Kounis acute coronary syndrome and thrombotic events post vaccination. RESULTS: The same key immunological pathophysiology mechanisms and cells seem to underlie COVID-19 cardiovascular complications and the anaphylaxis-associated Kounis syndrome. The myocardial injury in patients with COVID-19 has been attributed to coronary spasm, plaque rupture and microthrombi formation, hypoxic injury or cytokine storm disposing the same pathophysiology with the three clinical variants of Kounis syndrome. COVID-19-interrelated vaccine excipients as polysorbate, polyethelene glycol (PEG) and trometamol constitute potential allergenic substances. CONCLUSION: Better acknowledgement of the pathophysiological mechanisms, clinical similarities, multiorgan complications of COVID-19 or other viral infections as dengue and human immunodeficiency viruses along with the action of inflammatory cells inducing the Kounis syndrome could identify better immunological approaches for prevention, treatment of the COVID-19 pandemic as well as post-COVID-19 vaccine adverse reactions.

COVID-19: Famotidine, Histamine, Mast Cells, and Mechanisms.

SARS-CoV-2 infection is required for COVID-19, but many signs and symptoms of COVID-19 differ from common acute viral diseases. SARS-CoV-2 infection is necessary but not sufficient for development of clinical COVID-19 disease. Currently, there are no approved pre- or post-exposure prophylactic COVID-19 medical countermeasures. Clinical data suggest that famotidine may mitigate COVID-19 disease, but both mechanism of action and rationale for dose selection remain obscure. We have investigated several plausible hypotheses for famotidine activity including antiviral and host-mediated mechanisms of action. We propose that the principal mechanism of action of famotidine for relieving COVID-19 symptoms involves on-target histamine receptor H2 activity, and that development of clinical COVID-19 involves dysfunctional mast cell activation and histamine release. Based on these findings and associated hypothesis, new COVID-19 multi-drug treatment strategies based on repurposing well-characterized drugs are being developed and clinically tested, and many of these drugs are available worldwide in inexpensive generic oral forms suitable for both outpatient and inpatient treatment of COVID-19 disease.

COVID-19: Famotidine, Histamine, Mast Cells, and Mechanisms.

SARS-CoV-2 infection is required for COVID-19, but many signs and symptoms of COVID-19 differ from common acute viral diseases. Currently, there are no pre- or post-exposure prophylactic COVID-19 medical countermeasures. Clinical data suggest that famotidine may mitigate COVID-19 disease, but both mechanism of action and rationale for dose selection remain obscure. We explore several plausible avenues of activity including antiviral and host-mediated actions. We propose that the principal famotidine mechanism of action for COVID-19 involves on-target histamine receptor H2 activity, and that development of clinical COVID-19 involves dysfunctional mast cell activation and histamine release.

Mitotic and Meiotic Functions for the SUMOylation Pathway in the Caenorhabditis elegans Germline.

Meiosis is a highly regulated process, partly due to the need to break and then repair DNA as part of the meiotic program. Post-translational modifications are widely used during meiotic events to regulate steps such as protein complex formation, checkpoint activation, and protein attenuation. In this paper, we investigate how proteins that are obligatory components of the SUMO (small ubiquitin-like modifier) pathway, one such post-translational modification, affect the Caenorhabditis elegans germline. We show that UBC-9, the E2 conjugation enzyme, and the C. elegans homolog of SUMO, SMO-1, localize to germline nuclei throughout prophase I. Mutant analysis of smo-1 and ubc-9 revealed increased recombination intermediates throughout the germline, originating during the mitotic divisions. SUMOylation mutants also showed late meiotic defects including defects in the restructuring of oocyte bivalents and endomitotic oocytes. Increased rates of noninterfering crossovers were observed in ubc-9 heterozygotes, even though interfering crossovers were unaffected. We have also identified a physical interaction between UBC-9 and DNA repair protein MRE-11 ubc-9 and mre-11 null mutants exhibited similar phenotypes at germline mitotic nuclei and were synthetically sick. These phenotypes and genetic interactions were specific to MRE-11 null mutants as opposed to RAD-50 or resection-defective MRE-11 We propose that the SUMOylation pathway acts redundantly with MRE-11, and in this process MRE-11 likely plays a structural role.

Molecular evolution of Zika virus as it crossed the Pacific to the Americas.

Zika virus was previously considered to cause only a benign infection in humans. Studies of recent outbreaks of Zika virus in the Pacific, South America, Mexico and the Caribbean have associated the virus with severe neuropathology. Viral evolution may be one factor contributing to an apparent change in Zika disease as it spread from Southeast Asia across the Pacific to the Americas. To address this possibility, we have employed computational tools to compare the phylogeny, geography, immunology and RNA structure of Zika virus isolates from Africa, Asia, the Pacific and the Americas. In doing so, we compare and contrast methods and results for tree search and rooting of Zika virus phylogenies. In some phylogenetic analyses we find support for the hypothesis that there is a deep common ancestor between African and Asian clades (the "Asia/Africa" hypothesis). In other phylogenetic analyses, we find that Asian lineages are descendent from African lineages (the "out of Africa" hypothesis). In addition, we identify and evaluate key mutations in viral envelope protein coding and untranslated terminal RNA regions. We find stepwise mutations that have altered both immunological motif sets and regulatory sequence elements. Both of these sets of changes distinguish viruses found in Africa from those in the emergent Asia-Pacific-Americas lineage. These findings support the working hypothesis that mutations acquired by Zika virus in the Pacific and Americas contribute to changes in pathology. These results can inform experiments required to elucidate the role of viral genetic evolution in changes in neuropathology, including microcephaly and other neurological and skeletomuscular issues in infants, and Guillain-Barré syndrome in adults.

Zika Fetal Neuropathogenesis: Etiology of a Viral Syndrome.

The ongoing Zika virus epidemic in the Americas and the observed association with both fetal abnormalities (primary microcephaly) and adult autoimmune pathology (Guillain-Barré syndrome) has brought attention to this neglected pathogen. While initial case studies generated significant interest in the Zika virus outbreak, larger prospective epidemiology and basic virology studies examining the mechanisms of Zika viral infection and associated pathophysiology are only now starting to be published. In this review, we analyze Zika fetal neuropathogenesis from a comparative pathology perspective, using the historic metaphor of "TORCH" viral pathogenesis to provide context. By drawing parallels to other viral infections of the fetus, we identify common themes and mechanisms that may illuminate the observed pathology. The existing data on the susceptibility of various cells to both Zika and other flavivirus infections are summarized. Finally, we highlight relevant aspects of the known molecular mechanisms of flavivirus replication.

Zika Virus: Medical Countermeasure Development Challenges.

INTRODUCTION: Reports of high rates of primary microcephaly and Guillain-Barré syndrome associated with Zika virus infection in French Polynesia and Brazil have raised concerns that the virus circulating in these regions is a rapidly developing neuropathic, teratogenic, emerging infectious public health threat. There are no licensed medical countermeasures (vaccines, therapies or preventive drugs) available for Zika virus infection and disease. The Pan American Health Organization (PAHO) predicts that Zika virus will continue to spread and eventually reach all countries and territories in the Americas with endemic Aedes mosquitoes. This paper reviews the status of the Zika virus outbreak, including medical countermeasure options, with a focus on how the epidemiology, insect vectors, neuropathology, virology and immunology inform options and strategies available for medical countermeasure development and deployment. METHODS: Multiple information sources were employed to support the review. These included publically available literature, patents, official communications, English and Lusophone lay press. Online surveys were distributed to physicians in the US, Mexico and Argentina and responses analyzed. Computational epitope analysis as well as infectious disease outbreak modeling and forecasting were implemented. Field observations in Brazil were compiled and interviews conducted with public health officials.

Corn stover harvest increases herbicide movement to subsurface drains - Root Zone Water Quality Model simulations.

BACKGROUND: Crop residue removal for bioenergy production can alter soil hydrologic properties and the movement of agrochemicals to subsurface drains. The Root Zone Water Quality Model (RZWQM), previously calibrated using measured flow and atrazine concentrations in drainage from a 0.4 ha chisel-tilled plot, was used to investigate effects of 50 and 100% corn (Zea mays L.) stover harvest and the accompanying reductions in soil crust hydraulic conductivity and total macroporosity on transport of atrazine, metolachlor and metolachlor oxanilic acid (OXA). RESULTS: The model accurately simulated field-measured metolachlor transport in drainage. A 3 year simulation indicated that 50% residue removal reduced subsurface drainage by 31% and increased atrazine and metolachlor transport in drainage 4-5-fold when surface crust conductivity and macroporosity were reduced by 25%. Based on its measured sorption coefficient, approximately twofold reductions in OXA losses were simulated with residue removal. CONCLUSION: The RZWQM indicated that, if corn stover harvest reduces crust conductivity and soil macroporosity, losses of atrazine and metolachlor in subsurface drainage will increase owing to reduced sorption related to more water moving through fewer macropores. Losses of the metolachlor degradation product OXA will decrease as a result of the more rapid movement of the parent compound into the soil. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.

Data worth and prediction uncertainty for pesticide transport and fate models in Nebraska and Maryland, United States.

BACKGROUND: Complex environmental models are frequently extrapolated to overcome data limitations in space and time, but quantifying data worth to such models is rarely attempted. The authors determined which field observations most informed the parameters of agricultural system models applied to field sites in Nebraska (NE) and Maryland (MD), and identified parameters and observations that most influenced prediction uncertainty. RESULTS: The standard error of regression of the calibrated models was about the same at both NE (0.59) and MD (0.58), and overall reductions in prediction uncertainties of metolachlor and metolachlor ethane sulfonic acid concentrations were 98.0 and 98.6% respectively. Observation data groups reduced the prediction uncertainty by 55-90% at NE and by 28-96% at MD. Soil hydraulic parameters were well informed by the observed data at both sites, but pesticide and macropore properties had comparatively larger contributions after model calibration. CONCLUSIONS: Although the observed data were sparse, they substantially reduced prediction uncertainty in unsampled regions of pesticide breakthrough curves. Nitrate evidently functioned as a surrogate for soil hydraulic data in well-drained loam soils conducive to conservative transport of nitrogen. Pesticide properties and macropore parameters could most benefit from improved characterization further to reduce model misfit and prediction uncertainty.

Making vaccines "on demand": a potential solution for emerging pathogens and biodefense?

The integrated US Public Health Emergency Medical Countermeasures Enterprise (PHEMCE) has made great strides in strategic preparedness and response capabilities. There have been numerous advances in planning, biothreat countermeasure development, licensure, manufacturing, stockpiling and deployment. Increased biodefense surveillance capability has dramatically improved, while new tools and increased awareness have fostered rapid identification of new potential public health pathogens. Unfortunately, structural delays in vaccine design, development, manufacture, clinical testing and licensure processes remain significant obstacles to an effective national biodefense rapid response capability. This is particularly true for the very real threat of "novel pathogens" such as the avian-origin influenzas H7N9 and H5N1, and new coronaviruses such as hCoV-EMC. Conventional approaches to vaccine development, production, clinical testing and licensure are incompatible with the prompt deployment needed for an effective public health response. An alternative approach, proposed here, is to apply computational vaccine design tools and rapid production technologies that now make it possible to engineer vaccines for novel emerging pathogen and WMD biowarfare agent countermeasures in record time. These new tools have the potential to significantly reduce the time needed to design string-of-epitope vaccines for previously unknown pathogens. The design process-from genome to gene sequence, ready to insert in a DNA plasmid-can now be accomplished in less than 24 h. While these vaccines are by no means "standard," the need for innovation in the vaccine design and production process is great. Should such vaccines be developed, their 60-d start-to-finish timeline would represent a 2-fold faster response than the current standard.

Simulating nitrate-nitrogen concentration from a subsurface drainage system in response to nitrogen application rates using RZWQM2.

Computer models have been widely used to evaluate the impact of agronomic management on nitrogen (N) dynamics in subsurface drained fields. However, they have not been evaluated as to their ability to capture the variability of nitrate-nitrogen (NO(3)-N) concentration in subsurface drainage at a wide range of N application rates due to possible errors in the simulation of other system components. The objective of this study was to evaluate the performance of Root Zone Water Quality Model2 (RZWQM2) in simulating the response of NO(3)-N concentration in subsurface drainage to N application rate. A 16-yr field study conducted in Iowa at nine N rates (0-252 kg N ha(-1)) from 1989 to 2004 was used to evaluate the model, based on a previous calibration with data from 2005 to 2009 at this site. The results showed that the RZWQM2 model performed "satisfactorily" in simulating the response of NO(3)-N concentration in subsurface drainage to N fertilizer rate with 0.76, 0.49, and -3% for the Nash-Sutcliffe efficiency, the ratio of the root mean square error to the standard deviation, and percent bias, respectively. The simulation also identified that the N application rate required to achieve the maximum contaminant level for the annual average NO(3)-N concentration was similar to field-observed data. This study supports the use of RZWQM2 to predict NO(3)-N concentration in subsurface drainage at various N application rates once it is calibrated for the local condition.

Verifiable metamodels for nitrate losses to drains and groundwater in the Corn Belt, USA.

Nitrate leaching in the unsaturated zone poses a risk to groundwater, whereas nitrate in tile drainage is conveyed directly to streams. We developed metamodels (MMs) consisting of artificial neural networks to simplify and upscale mechanistic fate and transport models for prediction of nitrate losses by drains and leaching in the Corn Belt, USA. The two final MMs predicted nitrate concentration and flux, respectively, in the shallow subsurface. Because each MM considered both tile drainage and leaching, they represent an integrated approach to vulnerability assessment. The MMs used readily available data comprising farm fertilizer nitrogen (N), weather data, and soil properties as inputs; therefore, they were well suited for regional extrapolation. The MMs effectively related the outputs of the underlying mechanistic model (Root Zone Water Quality Model) to the inputs (R(2) = 0.986 for the nitrate concentration MM). Predicted nitrate concentration was compared with measured nitrate in 38 samples of recently recharged groundwater, yielding a Pearson's r of 0.466 (p = 0.003). Predicted nitrate generally was higher than that measured in groundwater, possibly as a result of the time-lag for modern recharge to reach well screens, denitrification in groundwater, or interception of recharge by tile drains. In a qualitative comparison, predicted nitrate concentration also compared favorably with results from a previous regression model that predicted total N in streams.

Predicting unsaturated zone nitrogen mass balances in agricultural settings of the United States.

Unsaturated zone N fate and transport were evaluated at four sites to identify the predominant pathways of N cycling: an almond [Prunus dulcis (Mill.) D.A. Webb] orchard and cornfield (Zea mays L.) in the lower Merced River study basin, California; and corn-soybean [Glycine max (L.) Merr.] rotations in study basins at Maple Creek, Nebraska, and at Morgan Creek, Maryland. We used inverse modeling with a new version of the Root Zone Water Quality Model (RZWQM2) to estimate soil hydraulic and nitrogen transformation parameters throughout the unsaturated zone; previous versions were limited to 3-m depth and relied on manual calibration. The overall goal of the modeling was to derive unsaturated zone N mass balances for the four sites. RZWQM2 showed promise for deeper simulation profiles. Relative root mean square error (RRMSE) values for predicted and observed nitrate concentrations in lysimeters were 0.40 and 0.52 for California (6.5 m depth) and Nebraska (10 m), respectively, and index of agreement (d) values were 0.60 and 0.71 (d varies between 0 and 1, with higher values indicating better agreement). For the shallow simulation profile (1 m) in Maryland, RRMSE and d for nitrate were 0.22 and 0.86, respectively. Except for Nebraska, predictions of average nitrate concentration at the bottom of the simulation profile agreed reasonably well with measured concentrations in monitoring wells. The largest additions of N were predicted to come from inorganic fertilizer (153-195 kg N ha(-1) yr(-1) in California) and N fixation (99 and 131 kg N ha(-1) yr(-1) in Maryland and Nebraska, respectively). Predicted N losses occurred primarily through plant uptake (144-237 kg N ha(-1) yr(-1)) and deep seepage out of the profile (56-102 kg N ha(-1) yr(-1)). Large reservoirs of organic N (up to 17,500 kg N ha(-1) m(-1) at Nebraska) were predicted to reside in the unsaturated zone, which has implications for potential future transfer of nitrate to groundwater.

Leveling the field: addressing health disparities through diabetes disease management.

OBJECTIVES: To examine the relationships among patient characteristics, labor inputs, and improvement in glycosylated hemoglobin (A1C) level in a successful primary care-based diabetes disease management program (DDMP). STUDY DESIGN: We performed subanalyses to examine the relationships among patient characteristics, labor inputs, and improvement in A1C level within a randomized controlled trial. Control patients received usual care, while intervention patients received usual care plus a comprehensive DDMP. METHODS: The primary outcome was improvement in A1C level over 12 months stratified by intervention status and patient characteristics. Process outcomes included the number of actions or contacts with patients, time spent with patients, and number of glucose medication titrations or additions. RESULTS: One hundred ninety-three of 217 enrolled patients (88.9%) had complete 12-month followup data. Patients in the intervention group had significantly greater improvement in A1C level than the control group (-2.1% vs -1.2%, P = .007). In multivariate analysis, no significant differences were observed in improvement in A1C level when stratified by age, race/ethnicity, income, or insurance status, and no interaction effect was observed between any covariate and intervention status. Among intervention patients, we observed similar labor inputs regardless of age, race/ethnicity, sex, education, or whether goal A1C level was achieved. CONCLUSIONS: Among intervention patients in a successful DDMP, improvement in A1C level was achieved regardless of age, race/ethnicity, sex, income, education, or insurance status. Labor inputs were similar regardless of age, race/ethnicity, sex, or education and may reflect the nondiscriminatory nature of providing algorithm-based disease management care.

Escherichia coli transport from surface-applied manure to subsurface drains through artificial biopores.

Bacteria transport in soils primarily occurs through soil mesopores and macropores (e.g., biopores and cracks). Field research has demonstrated that biopores and subsurface drains can be hydraulically connected. This research was conducted to investigate the importance of surface connected and disconnected (buried) biopores on Escherichia coli (E. coli) transport when biopores are located near subsurface drains. A soil column (28 by 50 by 95 cm) was packed with loamy sand and sandy loam soils to bulk densities of 1.6 and 1.4 Mg m(-3), respectively, and containing an artificial biopore located directly above a subsurface drain. The sandy loam soil was packed using two different methods: moist soil sieved to 4.0 mm and air-dried soil manually crushed and then sieved to 2.8 mm. A 1-cm constant head was induced on the soil surface in three flushes: (i) water, (ii) diluted liquid swine (Sus scrofa) manure 48 h later, and (iii) water 48 h after the manure. Escherichia coli transport to the drain was observed with either open surface connected or buried biopores. In surface connected biopores, E. coli transport was a function of the soil type and the layer thickness between the end of the biopore and drain. Buried biopores contributed flow and E. coli in the less sorptive soil (loamy sand) and the sorptive soil (sandy loam) containing a wide (i.e., with mesopores) pore space distribution prevalent due to the moist soil packing technique. Biopores provide a mechanism for rapidly transporting E. coli into subsurface drains during flow events.

Tethering recombination initiation proteins in Saccharomyces cerevisiae promotes double strand break formation.

Meiotic recombination in Saccharomyces cerevisiae is initiated by the creation of DNA double strand breaks (DSBs), an event requiring 10 recombination initiation proteins. Published data indicate that these 10 proteins form three main interaction subgroups [(Spo11-Rec102-Rec104-Ski8), (Rec114-Rec107-Mei4), and (Mre11-Rad50-Xrs2)], but certain components from each subgroup may also interact. Although several of the protein-protein interactions have been defined, the mechanism for DSB formation has been challenging to define. Using a variation of the approach pioneered by others, we have tethered 8 of the 10 initiation proteins to a recombination coldspot and discovered that in addition to Spo11, 6 others (Rec102, Rec104, Ski8, Rec114, Rec107, and Mei4) promote DSB formation at the coldspot, albeit with different frequencies. Of the 8 proteins tested, only Mre11 was unable to cause DSBs even though it binds to UAS(GAL) at GAL2. Our results suggest there may be several ways that the recombination initiation proteins can associate to form a functional initiation complex that can create DSBs.

Cherenkov radiation conversion and collection considerations for a gamma bang time/reaction history diagnostic for the NIF.

Bang time and reaction history measurements are fundamental components of diagnosing inertial confinement fusion (ICF) implosions and will be essential contributors to diagnosing attempts at ignition on the National Ignition Facility (NIF). Fusion gammas provide a direct measure of fusion interaction rate without being compromised by Doppler spreading. Gamma-based gas Cherenkov detectors that convert fusion gamma rays to optical Cherenkov photons for collection by fast recording systems have been developed and fielded at Omega. These systems have established their usefulness in illuminating ICF physics in several experimental campaigns. Bang time precision better than 25 ps has been demonstrated, well below the 50 ps accuracy requirement defined by the NIF system design requirements. A comprehensive, validated numerical study of candidate systems is providing essential information needed to make a down selection based on optimization of sensitivity, bandwidth, dynamic range, cost, and NIF logistics. This paper presents basic design considerations arising from the two-step conversion process from gamma rays to relativistic electrons to UV/visible Cherenkov radiation.